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About Faro

Faro is an AI memory layer that allows agentic systems to recall what it learned in the past. Faro currently outperforms industry leader Mem0 on the LoCoMo benchmark (94.1% vs 91.1%). Faro is the memory infrastructure that makes every AI agent more engaging and accurate to work with.

The Role

As an ML/AI researcher at Syntra, you will own the research geared at improving the Faro engine across areas such as: retrieval strategies, memory extraction quality, temporal reasoning, and the evaluation methodology.

You will design benchmarks, build the datasets and LLM judges that score them, run controlled experiments, and turn your research into production ready features. You will play a key role in keeping Faro ahead of its competitors and helping shape the overall product direction.

What you will Work On

• Benchmark datasets, ground truth, and evaluation harnesses
• LLM-judge scoring pipelines with confound controls
• Retrieval, chunking, and memory-extraction experiments
• Accuracy and latency improvements to the core recall engine
• Written recommendations backed by powered, reproducible measurements
• Research code that merges to main in small, production-safe PRs

Must-Haves

• 3+ years of applied ML/NLP research or equivalent industry R&D
• Strong Python capabilities
• LLM pipelines: prompt design, structured extraction, LLM-as-judge evaluation
• Embeddings + vector search (Qdrant, pgvector, Pinecone, or similar)
• Benchmark design: dataset construction, ground truth, statistically powered comparisons
• Engineering discipline: pytest, CI, code review, small reviewable PRs
• Self-starter or experienced with "startup pace"

Nice-to-Haves

• Memory-systems or RAG research (contextual retrieval, temporal reasoning, consolidation)
• Multi-provider LLM experience (OpenAI, AWS Bedrock, Cohere embeddings)
• Agent framework experience (LangChain, LlamaIndex, CrewAI, AutoGen)
• Publications or open-source evaluation and benchmark contributions
• Early-stage startup experience (Series A or earlier)

We will reach out and hold interviews on the week of September 7th, 2026. Thank you.

Job Description 

We are seeking a Multimedia Engineer for a long-term, full-time, remote project to join our engineering team, working on advanced audio/video streaming solutions for embedded platforms. The ideal candidate will have strong hands-on experience with GStreamer and a deep understanding of multimedia systems, media pipelines, and streaming technologies. 

Technical Requirements 

• 5+ years of software development experience in multimedia or system-level environments 
• Strong hands-on experience with GStreamer at the developer level (must-have), including: 

     - ​ building and debugging complex media pipelines 

     - working with elements, pads, caps, and plugins 

     - diagnosing latency, synchronization, and performance issues 

• Strong programming skills in C++ and Java for system-level or multimedia applications 
• Solid understanding of audio and video streaming protocols (RTP, RTSP, etc.) 
• Experience working with video and audio codecs (H.264, H.265, VP9, AAC, Opus, etc.) 
• Experience with Video4Linux (V4L2) Expe .;
• Experience with embedded platforms (Embedded Linux and/or Embedded Android) 
• Understanding of networking fundamentals: TCP, UDP, HTTP 
• Ability to debug complex issues across software layers (middleware, OS, hardware interaction) 
• Experience with version control systems (Git).
• Excellent problem-solving, critical thinking, and communication skills 

Nice to Have 

• Experience with Embedded Android / Android BSP (AOSP) 
• Familiarity with multimedia and graphics systems such as: 
• Android Audio / SurfaceFlinger 
• ffmpeg, VAAPI, OpenMAX, OpenGL 
• Experience with streaming technologies such as WebRTC 
• Experience with camera integration or camera subsystem customization 
• Knowledge of hardware-accelerated media pipelines 
• Scripting experience (Bash, Python) 

Responsibilities 

• Design, develop, and maintain multimedia middleware components 
• Build, integrate, and optimize GStreamer-based audio/video pipelines.
• Integrate media components with user-space applications and system services 
• Debug and resolve complex media issues related to performance, stability, and synchronization 
• Drive technical discussions and contribute to architecture decisions 
• Collaborate with hardware, platform, and application teams 
• Support board bring-up and hardware validation related to audio/video subsystems 

Our client is the leader in the Early Childhood Education (ECE) sector, providing the most widely used developmental assessment and curriculum system in the US. 

They are early in shaping how AI changes the way they build and operate software. They have active initiatives in AI tooling cost-management and agentic development workflows, but their direction is still forming and will keep evolving as the field does. 

They are not looking for someone to execute a fixed plan, they are looking for an experienced practitioner who can validate the direction we are setting, bring expertise we do not have in-house, stay ahead of what is emerging, and help us adjust and grow as the landscape shifts. This person is hands-on enough to build and prove things directly, and senior enough that we trust their judgment on where to place bets.

What you will do

• Act as a hands-on technical partner across AI engineering initiatives, currently spanning tooling cost management, model routing and selection, and agentic development workflows.
• Pressure-test the approaches they are considering, tell them where they are wrong or where a better path exists, and back it with evidence rather than opinion.
• Bring outside expertise and patterns from how other organizations are solving these problems, so they are not learning everything the expensive way.
• Track what is emerging across models, tooling, frameworks, and techniques, and translate it into concrete recommendations on what they should adopt, defer, or ignore.
• Build and run proofs of concept to validate ideas quickly, then help them decide what to operationalize.
• Help mature their agentic development workflow so engineering teams can adopt it, including model routing and token efficiency.
• Partner with Infrastructure and Security so that what they build fits their architecture and meets their data privacy obligations.
• Help them build internal capability, so the expertise compounds with their team and does not leave when the engagement ends.

Required background

• 5+ years in software, platform, or ML engineering, with recent, direct experience building and operating LLM-backed systems in production.
• Demonstrated breadth across the current AI engineering stack: models and their tradeoffs, inference cost dynamics, gateways and routing, agentic workflows, and the AI coding tool landscape.
• A track record of forming a point of view on fast-moving technical decisions and being right often enough to be trusted with them.
• Strong hands-on engineering ability. This person builds, benchmarks, and ships, not just advises.
• Comfort operating with ambiguity and early-stage direction; able to bring structure rather than wait for it.

• Cloud and infrastructure fluency (AWS preferred, including Bedrock).

   

Strongly preferred

• Experience helping an organization adopt AI-first engineering practices, not just individual tool use.
• Hands-on model evaluation and routing design, and exposure to AI cost governance.
• Experience in regulated data environments. 
• A habit of staying current through real practice (building, writing, contributing) rather than headlines.

What this role is not

• Not a fixed-scope implementation seat. The work will change as their direction evolves, and they want someone who helps drive that change.
• Not a data science or model training role. The focus is applied AI engineering, integration, and enablement.
• Not a manager. Individual contributor, hands-on, with influence earned through expertise. 

We are looking for a Business Analyst  with experience in Microsoft Dynamics Business Central to join our team. This role involves close collaboration with business stakeholders, analysis of processes, and implementation of ERP solutions.
 

🔧 Responsibilities

• Analyze and document business requirements
• Gather and formalize functional requirements
• Configure and support Microsoft Dynamics Business Central
• Participate in ERP implementation projects
• Communicate with stakeholders and end users
• Prepare documentation (BRD, SRS, user stories)
• Participate in testing and go-live activities
• Provide post-release support
   

✅ Requirements

• 3+ years of experience with Microsoft Dynamics Business Central (or NAV)
• Understanding of business processes (finance, supply chain, sales, procurement)
• Experience in writing business and technical documentation
• Experience in ERP implementations
• Strong communication skills
   

➕ Nice to have

• Experience with AL development or understanding of BC customization
• Experience with system integrations
• Microsoft Dynamics certifications 

Responsibilities:

• Own and support core ML infrastructure (MLflow, CVAT, GPU/CPU cloud instances, internal data tools).
• Assist Data Engineers with deploying and maintaining data pipelines.
• Act as the primary contact for ML and Data teams on infra-related requests.
• Improve reliability and efficiency by adding automation, monitoring, and tooling enhancements.
   

Must have:

• Knowledge of Python, Terraform, Docker, Linux.
• Hands-on experience with cloud environments (Azure prefered).
• Understanding of the end-to-end ML lifecycle (data → training → evaluation → deployment → monitoring).

Nice to have:

• Familiarity with Kubernetes.
• Experience with FFmpeg or GStreamer for video processing and streaming.
• Experience with model serving frameworks and inference formats (ONNX, TensorRT, OpenVINO, NVIDIA Triton).
• Experience deploying computer vision models, especially to edge/embedded devices (NVIDIA Jetson, Intel platforms, Raspberry Pi).

• Надаємо бронювання від мобілізації

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
   

We're looking for a hybrid BA + low-code automation engineer — someone who can talk to a bank's business stakeholders in the morning, and by evening have the process running as an executable workflow.

This is a role for people who think in state machines, not in Word documents.

⛔ Please DO NOT apply if you don't know

• What JSON is and how to work with it — you will live inside JSON payloads
• What Swagger is and how to test an API using Postman
• Anything about IT architecture, data types, sync vs. async, webhooks, and idempotency
• How to dive deep into a technical topic and come back with a solution
• How to model a real business process as states, transitions, and error branches

If your BA experience is limited to writing requirements and passing them to developers, this role is not for you. You will build.

We're looking for a problem solver, not a ping-pong player.

🤖 AI is mandatory, not a bonus

If you don't use AI in your daily work and can't work with AI agents — please don't write to us.

We build an AI Application Runtime, and we use AI to build it: requirement analysis, process decomposition, generating workflow logic, writing and reviewing JS/JSON inside nodes, drafting specs and documentation, building agent-driven automations for internal operations. Candidates without practical, demonstrable AI experience will not be considered.

Bring examples: your agents, your prompt libraries, your automations. We will look at them.

🚀 Project

Trigger Neobank Engine enables banks, fintechs, and telecoms to launch full digital banking products — onboarding, payments, cards, credit modules, corporate banking. Business logic is expressed as configurable, orchestrated processes rather than hardcoded services.

You will design and implement the processes that run real banking products.

🎯 What you'll do

• Elicit requirements from banks and fintech clients; convert vague business intent into precise, executable specifications
• Design process logic: state machines, decision trees, compensation and error-handling branches, SLAs and timeouts
• Build and maintain workflows in n8n / Corezoid / Node-RED — including JS code nodes, API calls, and data transformation
• Integrate external systems: core banking, processing, KYC/AML providers, payment rails, notification channels
• Design and document API contracts together with backend engineers
• Build AI-agent-based automations: routing, classification, document processing, operational assistants
• Test your own processes: Postman, log analysis, edge cases, retries, duplicate protection
• Write clean documentation: process diagrams, data flows, integration specs
• Support implementation teams during rollout and troubleshoot production behavior

🛠 Required

• 3+ years as a Business Analyst, Solution Analyst, Integration Engineer, or low-code developer
• Real, provable experience using AI tools and AI agents in daily work — mandatory
• Hands-on experience with at least one process/automation platform: n8n, Corezoid, Node-RED, Camunda, Temporal, Zapier/Make at a serious scale
• Confident with JSON, REST, webhooks, authentication (OAuth2, API keys, signatures)
• Ability to write basic JavaScript for data transformation inside workflow nodes
• Postman and Swagger as everyday tools
• SQL at a query level
• BPMN or equivalent process modelling
• Ability to structure your own work and drive a topic to closure without supervision
• Intermediate English or higher

⭐ Nice to have

• Fintech domain: payments, cards, onboarding, KYC/AML, ledgers, reconciliation
• Experience with Kafka or other message brokers
• Understanding of event-driven and microservice architecture
• Building your own AI agents / MCP tools / retrieval workflows
• Experience with server-driven UI or configuration-based platforms

📚 Mindset

• Ownership from requirement to production behavior
• AI-first: automate your own analyst work first
• Thinks about failure paths before happy paths
• Curious about what happens one layer below the abstraction

🎁 Offer

💻 100% remote

💵 Competitive salary in USD

⏰ Flexible schedule

🏦 A world-class fintech platform

🧠 Strong engineering culture and experienced leadership

🌍 Top-tier banks, fintechs and telecoms across emerging markets

🚀 Growth into Solution Architect or Product Owner

You will develop and automate CI/CD processes, configure monitoring, optimize infrastructure, ensure reliable service operation, and collaborate closely with development teams.

If you have strong DevOps expertise, experience with high-load systems, and a desire to build reliable infrastructure for products used by millions — we would be happy to welcome you to our team.

Responsibilities:

• Maintain, develop, and improve the company’s existing infrastructure
• Participate in the launch of new products and ensure the reliability and high availability of existing services
• Configure and maintain monitoring systems (Datadog, New Relic, Grafana), monitor infrastructure and microservices, and promptly respond to incidents, errors, and downtime
• Deploy, maintain, and optimize production and development environments for web applications
• Manage Infrastructure as Code (IaC) and ensure infrastructure reproducibility using Terraform
• Deploy and maintain services running in Kubernetes clusters
• Research emerging technologies, evaluate their applicability, and implement the most effective solutions
• Automate infrastructure and operational processes using Ansible, Terraform, and Docker
• Continuously improve professional skills, stay up to date with modern DevOps tools and best practices, and enhance technical expertise

Requirements:

• 1+ year of hands-on experience with Ansible
• Experience working with Terraform (Infrastructure as Code)
• Experience administering and operating Kubernetes
• Strong Linux administration skills, preferably Ubuntu-based systems
• Experience managing Bare Metal servers
• Hands-on experience with AWS cloud services (EC2, RDS, S3, CloudFront)
• Experience configuring and administering Cloudflare
• Experience setting up monitoring and metrics visualization systems (Grafana)
• Knowledge of and hands-on experience with MySQL 8 and Redis 6
• Basic knowledge of RabbitMQ administration
• Experience administering PHP 8+ (Laravel) projects
• Understanding of web infrastructure, networking concepts, and CI/CD processes will be considered an advantage

Are you passionate about building reliable, scalable, and highly available production systems? Do you enjoy solving complex engineering challenges through automation, observability, and software engineering?
Optimove is looking for a Senior Site Reliability Engineer (SRE) to join our global SRE organization. In this role, you'll partner with engineering teams globally to improve the reliability, scalability, and operational excellence of our cloud platform.
As a Senior SRE, you'll lead engineering-driven reliability initiatives by building automation, improving deployment processes, advancing observability, and driving operational excellence across our production environment.

Responsibilities
 

• Reliability Engineering – Design and implement solutions that improve the reliability, availability, and scalability of our production platform while proactively identifying and eliminating operational risks.
• Automation & Platform Engineering – Build internal tools and automation that eliminate manual operational work, improve engineering productivity, and streamline production workflows.
• Observability – Improve monitoring, alerting, dashboards, and production visibility while driving initiatives that reduce alert fatigue, improve incident detection, and strengthen operational insights.
• Production Rollouts – Design, improve, and support production deployment processes using modern release strategies such as Canary, Blue/Green, and Feature Flags to ensure safe and reliable releases.
• Production Reliability & Incident Response – Lead the investigation and resolution of critical production incidents, perform root cause analysis, and implement long-term preventive improvements that improve platform resilience and reduce recurring issues.
• On-Call & Operational Excellence – Participate in the team's on-call rotation, ensuring reliable production operations. Respond to critical incidents, collaborate with engineering teams during service disruptions, and drive engineering improvements, automation, and operational best practices that reduce operational toil and prevent future incidents.
• Cloud & Infrastructure – Design, maintain, and improve our Kubernetes-based cloud platform, CI/CD pipelines, and production infrastructure running on GCP and AWS.
• Engineering Partnership – Collaborate closely with Software Engineers, DevOps, DBAs, and Product teams to improve reliability across the software development lifecycle and promote SRE best practices.
   

Requirements
 

• 5+ years of experience in Site Reliability Engineering, Platform Engineering, DevOps, or Infrastructure Engineering.
• Hands-on experience operating Kubernetes in production environments.
• Strong experience working with public cloud platforms (GCP or AWS).
• Strong programming and scripting skills (Python preferred; Go or Bash are a plus).
• Experience designing and building automation and internal engineering tools.
• Experience working with CI/CD pipelines and modern deployment methodologies.
• Hands-on experience with observability platforms such as Datadog, Prometheus, or Grafana.
• Strong understanding of Linux, networking, distributed systems, and cloud-native architectures.
• Excellent troubleshooting, debugging, and root cause analysis skills.
• Strong communication skills and experience collaborating with globally distributed engineering teams.
   

Advantages
 

• Experience with Infrastructure as Code (Terraform, Ansible, etc.).
• Experience with messaging and distributed technologies such as Kafka, Pub/Sub, or Redis.
• Experience supporting modern deployment strategies such as Canary, Blue/Green, or Feature Flags.
• Familiarity with OpenTelemetry and modern observability tooling.
• Understanding of Site Reliability Engineering principles, including SLIs, SLOs, and error budgets.
• Experience working in large-scale SaaS production environments.
• Relevant cloud or Kubernetes certifications (GCP, AWS, CKA, CKAD).
  
  Why Join Us?
  Join a team where Site Reliability Engineering is treated as an engineering discipline—not just an operations function. You'll work on large-scale cloud infrastructure serving enterprise customers while building automation, improving observability, and enabling engineering teams to deliver software safely and reliably.
• You'll collaborate with a global SRE organization using modern cloud-native technologies, Kubernetes, distributed systems, and large-scale SaaS workloads. You'll have the opportunity to lead impactful reliability initiatives, influence engineering best practices, and solve complex production challenges that directly improve the experience of both customers and engineering teams.

Who are we?

Fuelfinance is on a mission to revolutionize financial management for early-stage startups, empowering them to take control of their finances and thrive. We recently raised $1M in Seed Funding from top-tier investors like Markus Villig (Bolt), John S. Kim (SendBird), Stratmind, and Bad Ideas funds, following 3 years of profitable, bootstrapped success. Trusted by businesses with over $200M in P&L, including Reface, Petcube, and Hampton, we’ve built a universal tool that brings clarity and insight to finance management.

With 38% of startups failing due to cash flow issues, our goal is to prevent these failures and unlock trillions in GDP growth. At Fuelfinance, we’re not just creating software — we’re safeguarding the future of thousands of startups. Join us and be part of this impact!

fuelfinance.me

www.instagram.com/fuelfinance

youtu.be/eI5VH2Ks9o4

Who are we searching for?

We're looking for an Enterprise Finance Engineer — someone who can design and implement AI-powered finance systems for our largest and most complex customers. This role sits at the intersection of Finance, Accounting, Systems, Automation, Integrations, and AI.

You'll work directly with CFOs, Finance Directors, Controllers, IT teams, and finance teams to redesign finance operations through AI, automation, and system integrations. You'll own a small number of large, strategic customers end-to-end — from understanding business processes to designing scalable solutions and continuously improving them as the business evolves.

This isn't a role for someone who wants repeatable implementations or well-defined requirements. Every customer is different. You'll navigate ambiguity, work with demanding stakeholders, and solve unique technical problems without predefined playbooks. If that energizes you, we'd love to meet you.

What are your responsibilities?

• Design and implement AI-powered finance systems for enterprise customers
• Lead discovery sessions to understand finance processes and identify automation opportunities
• Build workflows for reporting, forecasting, financial controls, reconciliations, and planning
• Design integrations across ERP, accounting, CRM, payment, BI, and data platforms
• Translate finance requirements into scalable workflows, automations, and system architecture
• Build AI agents, validation logic, and automation frameworks that reduce manual work
• Partner with Engineering on APIs, integrations, and workflow orchestration
• Coordinate across Engineering, Product, and Customer Success as the trusted technical partner for your customers
• Continuously improve customer solutions as business needs evolve

What are the preferred requirements for the role?

• 10+ years implementing finance systems, automations, or enterprise finance operations
• 1+ year building AI-powered automations, agents, workflows, or internal AI tools
• Hands-on experience with APIs, system integrations, automation platforms, and data warehouses
• Experience working with enterprise or multi-entity organizations (multiple stakeholders, legacy systems, changing requirements, long implementation cycles)
• Proven experience leading implementation projects end-to-end — discovery, solution design, rollout, training, and support
• Fluent English
• Strong understanding of finance and accounting processes, including financial close, reporting, FP&A, revenue, AP/AR, and financial controls
• Ability to understand how financial data flows across systems and departments
• Experience with ERP, accounting, or billing systems
• Proven impact in numbers: hours saved, manual work reduced, faster reporting, or fewer errors
• Excellent communication skills and experience working directly with senior finance stakeholders
• Strong systems thinking — the ability to see the bigger picture and break complex finance processes into scalable, maintainable, reusable solutions
• Ownership: taking full responsibility from problem discovery through implementation and post-launch optimization
• Learning agility: quickly mastering new AI tools, technologies, and approaches
• Strong problem-solving under ambiguity, with the judgment to make trade-offs and prioritize
• Strong drive to eliminate repetitive manual work
• Proactivity and a high level of responsibility
• Ability to work in a fast-paced environment

Will be a plus:

• Python or other scripting experience
• SQL and the ability to retrieve and validate financial data independently
• Experience with tools like NetSuite, QuickBooks, Xero, Stripe, Salesforce, HubSpot, Zuora, BigQuery, Snowflake, PostgreSQL, Looker, Power BI, Tableau, Zapier, Make, n8n, or Workato
• Understanding of enterprise architecture — security, scalability, governance, and integration patterns
• Experience working with US-based clients or startups

Reporting Structure: reporting to the Head of FP&A

Recruitment Process:

• Soft skills interview with the recruiter
• Test task
• Hard skills interview with the Head of FP&A
• Culture fit interview with the Head of FP&A/VP of Operations

Why work with us?

• Build the future of finance work — design AI-native finance operations, not just maintain them
• Rapid skills improvement (you'll work with multiple client businesses with different models and challenges)
• Growth opportunities according to our seniority grading (it comes with a compensation increase)
• Flexible schedule and time-off policy
• 18 days of paid vacation per year, paid sick leaves

MacPaw is a software company that develops and distributes software for macOS and iOS. Today, we have 20 million active users across all our products, and every 5th Mac on Earth has our product installed.

At MacPaw, we believe humans and technology can reach their greatest potential together.

We gather open-minded people who support each other and aspire to change the world around us, making millions of people’s lives easier with technology.

Our flagship products include CleanMyMac, Setapp, ClearVPN, Moonlock, and more. Now, we’re stepping into an important new stage: launching a product ecosystem with a new AI Mac Assistant — Eney.

We are expanding our team and looking for a Data Engineer to help us build a scalable, reliable data architecture.

In this role, you will build reliable data pipelines, design clear domain models, and optimize our data warehouse. We value a practical, problem-solving mindset — someone who easily navigates ambiguous requirements, brings structure to complex tasks, and takes ownership of their solutions.

In this role, you will:

• Build and support Airflow pipelines to ingest data from third-party sources (APIs, payment providers, ad networks) with retries, backfills, and quality checks.
• Work directly with Analytics Engineers and product teams to translate ambiguous business requests into reliable data models.
• Design and implement fact and dimension tables in dbt using dimensional modeling principles.
• Migrate existing SQL transformations into dbt models, adding tests and documentation.
• Refactor the current dbt project: improve layer structure, standardize naming conventions, and set up CI checks.
• Optimize slow or costly warehouse queries and materializations.
• Evaluate table formats and set up initial ingestion flows for our Data Lakehouse prototype.

Skills you’ll need to bring:

• Strong proficiency in Python and advanced SQL, including complex transformations, window functions, and query optimization.
• Proven experience building and orchestrating ELT/ETL pipelines using Airflow.
• Solid experience with dbt for data modeling, testing, documentation, and managing project structure.
• Good understanding of dimensional modeling concepts, Kimball methodology, star/snowflake schemas, and SCDs.
• Practical experience working with cloud data warehouses (preferably BigQuery, Redshift, or Snowflake) and Cloud Storage.
• Hands-on experience with Docker, Git workflows, and basic cloud/containerized environments.
• A problem-solving mindset with the ability to handle ambiguous requirements, communicate effectively with stakeholders, and use AI/LLM tools (like Claude) to speed up delivery.
• At least an Intermediate level of English and fluent Ukrainian.

As a plus:

• Experience with change data capture (CDC) tools and patterns (e.g., Debezium).
• Background in building and optimizing large-scale data processing jobs with PySpark.
• Experience with real-time data processing using message brokers like Kafka or RabbitMQ.
• Experience with stream processing frameworks (Flink, Kafka Streams).

What we offer:

• We are a Ukrainian company, and we stand with Ukraine against the russian aggression
  We maintain workplaces for the mobilized Macpawians and provide financial support to colleagues or their families affected by the war. Here, you can also read about the MacPaw Foundation, which intends to help save the lives of Ukrainian defenders and provide relief to as many civilians as possible.
• We are committed to our veterans
  Our Veteran Career and Empowerment Program is designed to ensure our veterans and active military personnel receive the recognition, support, and opportunities they deserve.
• Hybrid work model
  Whether to work remotely or at the hub is entirely up to you. If you decide to mix it, our Kyiv office, which works as a coworking space, is open around the clock. The office is supplied with UPS and Starlink for an uninterrupted work process.
• Your health always comes first
  We guarantee medical insurance starting on your first working month. For those abroad, you can receive a yearly Medical insurance allowance as compensation for managing your medical expenses.
• Flexible working hours
  You can choose a schedule that is comfortable for you. No one here tracks your clock in/out because MacPaw is built on trust and cooperation.
• Space to grow both professionally and personally
  Education opportunities to grow both hard and soft skills, annual development reviews, and internal community.
• Teams we are proud of
  We build honest, transparent, and reliable relationships within teams. Every Macpawian can improve processes and implement their ideas. We encourage open and constructive feedback and provide training for Macpawians on giving and receiving feedback.
• Office designed for people (and pets)
  Our office has it all: a spacious workplace with enough room for sitting up, lying down, and running around; a gym for recreation; cozy kitchens; a sleeping/meditation room; and a terrace with a view where we throw summer parties. Also, we have two cats living in the office, and you are welcome to bring your pets to the office (we have separate floors for cats and dogs).
• Time-off policy that covers life’s needs
  Convenient personal time-off policy to help you take care of essential matters in your personal life, and parental leaves. On top of all that, sabbaticals are open after 5 years of being with MacPaw.
• Join social initiatives with MacPawCares
  MacPaw participates in numerous humanitarian aid and charity projects across many fields, and you are welcome to jump in to make the world a better place.
• We’re an equal-opportunity employer. Here is a safe place for applicants of all backgrounds
  We are hiring talented humans. Meaning with all our variety of backgrounds and identities, including service members and veterans, women, members of the LGBTQIA+ community, individuals with disabilities, and other often underrepresented groups. MacPaw does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
  
  *Some benefits are under development, and new adjustments are possible.

About the Role
 

 We are looking for an experienced Database Administrator to help migrate and modernize our PostgreSQL and MySQL database environments, including onto Kubernetes. You will plan and execute database migrations, then manage, maintain, and optimize these databases across multiple clusters ensuring reliability, performance, and availability.
 

Responsibilities
 

- Administer and maintain PostgreSQL and MySQL databases in production and lower environments

- Deploy, manage, and troubleshoot database workloads

- Implement and manage database replication, high availability, and failover strategies

- Plan and execute database migrations

- Monitor database performance, identify bottlenecks, and implement tunning improvements

- Manage backup and recovery procedures

- Maintain database infrastructure as code using Git-based workflows
 

Required Skills & Experience 
 

- PostgreSQL — Strong production experience with administration, performance tuning, and troubleshooting

- MySQL — Strong production experience with administration, performance tuning, and troubleshooting

- Kubernetes — Hands-on experience running stateful database workloads on Kubernetes

- Replication — Experience configuring and managing streaming replication, logical replication, and MySQL replication topologies

- Migrations — Proven track record of planning and executing database migrations (version upgrades, platform migrations, schema migrations)

- Backup & Recovery — Experience with backup strategies, point-in-time recovery, and disaster recovery planning

- Git — Comfortable working with Git for version control, pull requests, and collaborative workflows

- Monitoring — Experience with database monitoring and alerting (Prometheus, Grafana, or similar)

- Linux — Solid understanding of Linux systems administration

 

Preferred Skills & Experience 
 

- CloudNativePG (CNPG) — Experience deploying and managing PostgreSQL using the CNPG operator on Kubernetes

- Percona — Experience with Percona Server for MySQL, Percona XtraBackup, or Percona Kubernetes Operators

- Infrastructure as Code — Familiarity with Helm, ArgoCD, or similar GitOps tooling

- Cloud Platforms — Experience with managed database services or Kubernetes on AWS, GCP, or OCI

- Connection Pooling — Experience with PgBouncer, ProxySQL, or similar

- Security — Understanding of database encryption, access control, and secrets management
 

We are looking for a Quant Researcher to take ownership of systematic trading strategies across crypto markets.

You will be expected to take ideas from hypothesis through data analysis, backtesting, execution design and live trading — and ultimately take responsibility for PnL.

What you will own

• Research of short-horizon and trading opportunities
• Market microstructure analysis 
• Strategy design and validation
• Execution logic and live performance analysis
• Strategy monitoring and iteration after deployment

What we care about

We care substantially more about how you think than about your job title. Strong candidates will typically have experience with some combination of:

• systematic / quantitative trading
• crypto market microstructure
• high-frequency or short-horizon signals
• lang for research
• large market datasets
• realistic backtesting and simulation
• execution analysis
• live trading systems

Compensation and ownership

This is a performance-driven role. Your upside is directly linked to the live performance of the strategies you research, deploy and own.

Strategies that pass validation receive a meaningful initial capital allocation and are scaled based on live performance, capacity and risk.

Meaningful contributions to the boutique’s infrastructure may be compensated separately on a fixed basis.

Before applying:

• Market microstructure knowledge is a hard requirement. If you cannot reason confidently about it, please do not apply.
• You must be comfortable designing and validating strategies operating on sub-second horizons.
• Generic, templated or LLM-generated technical answers presented as your own work will result in immediate rejection.
• Applications that do not meet these requirements may be rejected without individual feedback.

This role is not suitable for candidates whose experience is limited to OHLC-based strategies.

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

OU’s: Currently, Nuero, Cardio, Diabetes is the OU that HDP data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

As a System Engineer within the Company Research & Systems Engineering team, you will have the opportunity to work on cloud-based solutions with a strong focus on AWS, Data Engineering, and scalable data platforms. You will collaborate with cross-functional engineering teams to design, develop, integrate, and maintain reliable cloud-native systems and data workflows.

In this role, you will contribute to building and evolving AWS-based architectures, data processing pipelines, and integrations across distributed systems. You will develop a strong understanding of end-to-end system architecture, data flows, infrastructure, and operational requirements, helping to drive technical implementation and delivery throughout the software development lifecycle.

You will work closely with software engineers, data engineers, architects, and other stakeholders to ensure that solutions are scalable, secure, maintainable, and aligned with both technical and business requirements.

• 3+ years of experience in System Engineering, Software Engineering, Cloud Engineering, Data Engineering, or a related technical role.
• Strong software development experience with Python.
• Hands-on experience designing, developing, or supporting solutions on AWS.
• Experience with data engineering concepts and technologies, including data ingestion, ETL/ELT, transformation, validation, and data processing pipelines.
• Strong SQL skills and experience working with relational and/or NoSQL databases.
• Experience with REST APIs, service integrations, and distributed application architectures.
• Understanding of cloud-native architecture principles and modern software development practices.
• Experience troubleshooting applications and distributed cloud systems and performing root cause analysis.
• Experience with Git and modern CI/CD development workflows.
• Strong analytical and problem-solving skills with the ability to understand complex systems and data flows.
• Ability to work effectively with software, data, cloud, and machine learning engineering teams.
• BA/BS in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with AWS data services such as S3, Glue, Athena, EMR, or similar technologies.
• Experience with Amazon SageMaker and machine learning development or deployment workflows.
• Experience with Infrastructure as Code using AWS CloudFormation, Terraform, or AWS CDK.
• Experience with AWS monitoring and observability services such as CloudWatch and CloudTrail.
• Experience working in Agile/Scrum development environments.

Job responsibilities

• Work with engineering and cross-functional stakeholders to gather, analyze, clarify, and document business, functional, and non-functional requirements, translating them into clear system and technical requirements.
• Define system requirements, interfaces, data flows, integration requirements, acceptance criteria, and technical constraints for cloud-based software components, data platforms, and integrations.
• Maintain requirements throughout the development lifecycle, ensuring traceability between business needs, system requirements, technical design, implementation, and validation.
• Identify gaps, dependencies, assumptions, and potential technical risks in requirements and work with stakeholders to resolve them before and during implementation.
• Design and contribute to scalable AWS-based architectures supporting data ingestion, processing, transformation, storage, and distribution.
• Analyze data and system behavior to support architecture, implementation, performance, and product decisions.
• Collaborate with Data Engineering, Software Engineering, Cloud Engineering, DevOps, and Architecture teams to design and integrate end-to-end cloud solutions.
• Support operational monitoring, logging, alerting, and troubleshooting of cloud applications and data processing workflows.
• Contribute to system architecture and technical design discussions, including scalability, reliability, security, performance, and cost considerations.
• Participate in technical and requirements reviews to ensure solutions meet defined requirements, engineering standards, cloud best practices, and established software development processes.
• Support continuous improvement of cloud infrastructure, data pipelines, deployment processes, requirements management, and engineering practices throughout the software development lifecycle.

We are looking for a talented Agentic Full stack Engineer (AI-Native Delivery) with 3+ years of commercial full stack experience, to join an established, revenue-generating B2B platform for the materials industry.

This is not a "write code with AI" role — it's an operate AI agents role: decompose work, fan it out to parallel coding agents, verify adversarially, ship across the stack.

JOB REQUIREMENTS:

Must have:

• 3+ years of commercial fullstack development experience (React + Node.js/TypeScript, or Python)
• Hands-on, practical experience directing multiple AI coding agents in parallel — isolated worktrees/branches, adversarial verification of agent output, spec-driven development, and building reusable AI skills/hooks/commands for recurring workflows 
• Working knowledge of PostgreSQL and basic understanding of cloud infrastructure (Terraform/AWS)
• Ability to work fully autonomously and communicate directly with an English-speaking client team without a manager in between
• English — Upper-Intermediate or higher

Nice to have:

• Experience with SAP / enterprise ERP integration (RFC/BAPI, ABAP, customer & order master data)
• Experience in multi-tenant / B2B SaaS platforms
• Familiarity with compliance frameworks (GDPR, SOC 2, ISO 27001)
• Experience building internal tooling for other engineers
• Design-system literacy

Key Responsibilities:

• Full-stack development across the client's platform — from a React component to a Postgres row-level-security policy to a Terraform module
• Cross-boundary root-cause debugging: auth, pagination, dependency conflicts, integration mismatches
• Turning recurring tasks into reusable AI agent skills, hooks, and commands so the next run is faster
• Proving results with concrete evidence — fixtures, payloads, read-back records — rather than relying on a green CI badge alone

PROJECT

Customer: Established, revenue-generating international platform for the materials industry, backed by a large global industrial distribution group.

Type: B2B SaaS / marketplace platform.

Product: The platform serves as a digital backbone for companies across the materials industry — chemicals, polymers, elastomers, rubber — replacing a patchwork of separate CRMs, ERPs, and spreadsheets with one connected system that turns commercial interactions and physical assets into structured, usable data.

Market: Global materials/chemicals industry, client team based in the US.

Stage: Mature, actively growing platform with an established engineering team (not a from-scratch build).

Project team: 3 developers, 2 QA, 1 DevOps on the delivery side, plus a dynamic client-side team. 

Work schedule: Full-time, full remote 

INTERVIEW STAGES:

• 1-st stage — Call with the Recruiter
• 2-nd stage — Interview with the technical specialist and the recruiter

• 3-rd stage —  Interview with the client

   

OUR BENEFITS:

• Projects with modern JS stack (React.js, React Native, Angular, Node.js)
• Strong JavaScript community at the company (90+ developers)
• Work from anywhere (fully remotely or in our office)
• Paid vacations and sick-leaves, additional days-off, relocation bonus
• Wellness: Medical insurance/ sport compensation/ health check-up+flu vaccination at your choice
• Education: regular tech-talks, educational courses, paid certifications, English classes
• Fun: own football team, budget for team-lunches, branded gifts
• One of the best IT employers in Lviv (or IT service companies in Ukraine) based on DOU rating