Jobs ML / AI Engineer

About the Role

We're a fast-moving consultancy building AI-powered solutions for multiple clients across industries. Our projects move quickly, and we rely on engineers who embrace AI in their workflows to deliver features and fix bugs at speed. This role will begin as a contract, part-time position, with the opportunity to grow into a full-time role as we scale.

What You'll Do

• Build and maintain client-facing projects in Next.js and Node.js
• Develop responsive front-end features using React, HTML, and CSS
• Build and maintain server-side APIs and integrations with external systems
• Use AI-first tools (Claude Code, OpenAI Codex, Cursor, Windsurf) to accelerate development
• Write and debug Bash scripts for automation and CLI-based workflows
• Use Python for scripting, API integrations, and backend tasks when needed
• Ship new features, fix bugs, and improve performance across multiple projects
• Contribute to architecture and deployment decisions on cloud platforms
• Work across multiple projects at once, balancing priorities and client needs
• Integrate with third-party APIs for multiple clients, adapting to different systems and data structures
• Move fast, experiment, and thrive in a builder environment where the terminal and AI tools are central to the workflow

What We're Looking For

• Strong software engineering fundamentals with experience in JavaScript/TypeScript
• Skilled in React, HTML, CSS, and building modern front-end experiences
• Experience building and consuming server-side APIs (REST, GraphQL, etc.)
• Proficiency in Bash scripting and comfort working in the terminal/CLI
• Experience with Python for automation, scripting, or backend integrations
• Experience deploying on cloud platforms (Vercel preferred, or AWS, Azure, GCP)
• Familiarity with modern database platforms (Postgres, Mongo, Supabase, Firebase)
• Hands-on use of AI-first tools (Claude Code, OpenAI Codex, Cursor, Windsurf) in real workflows
• Skilled at building and debugging API integrations for different platforms and clients
• A builder mindset: enjoys hacking, experimenting, and shipping quickly
• A quick learner who thrives in fast-paced environments and takes ownership
• Knowledge of authentication systems (OAuth, SSO, JWT, etc.)
• Ability to manage and contribute to multiple projects simultaneously

Nice to Have

• Consulting or client-facing project experience
• Exposure to AI/ML integrations beyond code acceleration

Our Tech Stack

Frontend/Backend

Next.jsNode.jsReactHTMLCSS

Languages

JavaScript/TypeScriptPythonBash

Databases

PostgreSQLMongoDBSupabaseFirebase

Cloud Providers

VercelAWSAzureGoogle Cloud

AI Tools

Claude CodeOpenAI CodexCursorWindsurf

We are looking for a Blockchain Software Engineer with strong experience in Java, data-intensive systems, and distributed architectures, who enjoys working with blockchain data at scale.

In this role, the focus is on building robust backend systems and data pipelines that process, enrich, and serve blockchain data reliably and efficiently.

We value engineers with a solid foundation in computer science, who can reason about complex systems, understand trade-offs, and take ownership of production-grade infrastructure.

What you will do

• Design and develop Java-based backend services for blockchain data processing.
• Build and operate on-chain and off-chain data pipelines handling large volumes of events.
• Transform blockchain data (blocks, transactions, logs, state changes) into structured, analytics-ready datasets.
• Develop microservices deployed on Kubernetes (K8S) with a focus on stability and scalability.

• Work with streaming and batch processing systems (Kafka, Spark).

   

What we expect from you

• 3+ years of professional experience with Java.
• 5+ years of experience building data-intensive or data engineering systems.
• Strong fundamentals in algorithms, data structures, and distributed systems.
• Hands-on experience with high-throughput systems.
• Familiarity with technologies such as:
  • Kafka, Spark
  • ClickHouse, Snowflake, Redis (or similar)
  • Kubernetes (K8S), Airflow
• Ability to work independently and take responsibility for systems end to end.
• Bachelor’s degree in Computer Science or a related field.

Nice to have

• Experience with blockchain or Web3 infrastructure.
• Understanding of blockchain internals (blocks, transactions, consensus, re-orgs).
• Background in fintech, trading, or low-latency systems.
• Experience with analytics platforms or indexing services.

US Company is searching for a couple of Senior MLOps Engineers into a complex, enterprise-level project for maintaining of Multi AI Agentic platform. Interesting project with cutting edge technologies, distributed team, full-time, an official contract. Remote work, flexible schedule.

Brief project description:

• The product is SaaS, which allows multiple functions for sustainability & operational risk management. The project is dedicated for developing and maintaining of AI Center of Excellence.

Key areas of responsibility:

• Support application infrastructure to ensure platform is optimized for performance and reliability.
• Build and maintain supporting infrastructure for cloud environments and applications.
• Lead the design and engineering of software systems for the AI/ML Platform, contributing to the full ML development life cycle
• Identify and implement opportunities to automate and streamline ML development processes, fostering efficiency and effectiveness
• Building and Managing enterprise AI solutions using Azure AI Foundry & Azure's integrated platform (Azure OpenAI, AI Search, Prompt Flow),
• Use a wide range of Azure resources to implement scalable, reliable and cost-efficient services.
• Work side by side with your engineers, guiding critical projects, using your subject matter expertise to solve complex problems.
• Perform and automate system administration services including installation, configuration, maintenance, and disaster recovery
• Identify system level issues related to OS configuration and virtual hardware bottlenecks.
• Automation, auditing, and other tooling for security, compliance, and resource usage - Monitor and improve processes for all deployments.
• Take ownership of operational excellence to establish and maintain business focused KPI’s. Use these metrics not only as a basis for positive transformation, but also as a visible representation of your team’s success.
• Maintain and take ownership of your tasks each sprint ensuring time worked is logged and details are added.

Required skills (at least one or more for each category):

• Excellent communication and collaboration skills.
• Ability to communicate effectively with multiple disciplines.
• Strong analytical skills with the ability to drive reliability improvements.
• Proven experience designing, implementing, and managing infrastructure for AI/ML or HPC workloads.
• Proven success managing and optimizing CI/CD for an Azure-based SaaS application.
• Hands-on-experience with common DevOps tools, including Azure DevOps.
• Strong scripting skills with at least PowerShell or Bash.
• Experience with configuration management tools like Terraform.
• Working knowledge of version control/source code management tools.
• Experience working in an agile software development life cycle.
• Working knowledge of databases including SQL and NoSQL
• Strong knowledge of web server configuration and management like IIS or Tomcat.
• Working knowledge of local and wide area networking and associated technologies, e.g. switches, routers, firewalls, VPNs.
• Strong understanding of security principles.
• Bachelor’s Degree in Computer Science or similar area of study.
• Experience working in a technical fast paced environment with high demand and high standards.
• Ability to assimilate information quickly under pressure.
• Strong planning skills to ensure business expectations are met and projects are delivered on time.

Tech Stack:

• Understanding machine learning frameworks and libraries such as TensorFlow, PyTorch, or sci-kit-learn and their deployment in production environments is a plus.
• Cloud-based networking (VNETs, NSGs, Route Tables, Hub/Spoke based architecture, Private Endpoints, etc)
• Strong understanding of CI/CD (YAML and Classic Pipelines)
• PaaS (Web Apps, Function Apps, Storage Accounts, Key Vaults, Azure Redis Cache, Azure Service Bus, API Management, Azure Data Factory, Azure Databricks)
• Monitoring (New Relic, LogEntries, Rapid7, Azure Monitoring, etc)
• Some experience with Containers/Docker either for a microservice based architecture or Service Orientated etc
• Git, ARM, Terraform, Ansible, Azure CLI or similar.
• JavaScript, React, C#, Java, PowerShell, Bash or similar.

Work conditions:

• Distributed team, remote work.
• Kanban or scrum approach, 5-6 team members / team.
• Full-time (40 hours per week).
• Official contract: salary, sick-leave days, holidays, vacations.

Hiring process:

• Step 1 - preliminary interview (main questions) - 30 mins
• Step 2 - internal tech interview (tech questions) - 40-50 mins
• Step 3 - tech interview with team leader and architect - 1 hour

I am looking for a candidate for the #1 international medical tourism platform that helps patients from all over the world find the best clinics and doctors. 

We are currently scaling our SEO processes for 9 languages and looking for a Python AI Developer who will help us automate content creation and data processing using LLMs.
 

What you will do:

• Create AI agents & workflows: Automating generation, optimization, and verification of content, among other tasks.
• Build RAG systems: Ensuring our AI solutions are based on up-to-date medical data and Bookimed expertise.
• Develop ETL processes: Data parsing, processing large arrays of information, and integration via API.
• Rapid Prototyping: Transforming ideas from the SEO team into working tools (from idea to MVP in 2–3 days).
• Scaling: Moving successful experiments into stable production.
   

Our Tech Stack:

• Languages: Python (Clean code, fast delivery).
• AI/LLM: OpenAI API (GPT-4), Claude API, LangChain/LlamaIndex.
• Data/DB: SQL (PostgreSQL), Vector DBs (Pinecone/Weaviate), Pandas.
• Automation/Ops: n8n (or Make), Docker, Git, REST API & Webhooks.
   

You are our ideal candidate if:

• You write Python “automatically”: Fast, clean, and without unnecessary complications.
• You have a “Bias to Action”: You are a pragmatist who prefers a working solution “today” over an ideal architectural masterpiece “in a month.”
• Experienced with LLMs: You understand the difference between models, are skilled in Prompt Engineering, and know how RAG works in practice.
• API Master: REST, rate limits, error handling — this is your daily toolkit.
• Independent: You can figure out the documentation for a new library and implement it in an evening.
  
   

Will be a plus:

• Understanding of SEO principles (or readiness to dive in quickly).
• Experience working with large volumes of data (millions of rows).
• Understanding of basic statistics (A/B tests).
  
   

What we provide for your development and comfortable cooperation:

• Fully remote work — work from anywhere in Ukraine or the world.
• Medical insurance (after 3 months of work).
• Compensation for sports and coworking expenses.
• 22 paid vacation days per year.
• 10 paid sick days.
• 8 fixed extra days off for national holidays.
• Competitive market salary (discussed individually).
• Bonuses for achieving KPIs and successful project implementation.
• Provision of all necessary equipment.
• Full onboarding and constant support from the team.
• Funding and access to premium AI models and SEO tools.
• Budget for courses and certifications in automation.

Imagine enhancing an AI assistant that already lives on Macs — one that truly understands its users, adapts to their habits, and helps them stay focused on what matters most. Eney is MacPaw’s AI companion for macOS, designed to organize, automate, and simplify users’ daily workflows.

Now, we’re taking Eney to the next level — making it smarter, faster, and capable of running advanced LLMs directly on-device. As a Senior ML Engineer, you’ll fine-tune and optimize the latest LLMs using cutting-edge techniques (LoRA, Q-LoRA, DPO, GRPO), build scalable ML pipelines, and shape how AI seamlessly integrates into everyday Mac experiences.

In this role, you will:

• Train and fine-tune LLMs (e.g., LLaMA, Gemma, Qwen) for specialized tasks (such as function calling, charting, parameter parsing) and ensure their effective deployment across diverse environments, including on-device (MLX)
• Develop and apply model optimization and compression techniques (e.g., dynamic pruning, quantization) to enable high-performance on-device inference
• Conduct rigorous evaluation and benchmarking of LLMs to measure performance, accuracy, and efficiency across different setups
• Adapt LLMs for domain-specific tasks using techniques such as prompt engineering, adapter-based fine-tuning (PEFT), and multi-modal extensions.

Skills you’ll need to bring:

• Strong background in classical ML and NLP
• Solid knowledge of deep learning, going beyond just LLMs (e.g., CNNs, RNNs, Transformers, Autoencoders)
• Proficiency in Python and deep learning frameworks (e.g., PyTorch)
• Deep experience with LLMs: training large and small models using various techniques (fine-tuning, post-fine-tuning, DPO, GRPO)
• Practical experience with LoRA / Q-LoRA and other adapter-based fine-tuning methods
• Knowledge in model optimization (pruning, quantization), evaluation, and deployment
• Ability to design and automate ML pipelines with a focus on scalability and maintainability
• Upper-intermediate English & fluent Ukrainian

As a plus:

• Experience working with multi-modal data: structured/tabular, images, audio, or video
• Experience in synthetic data generation
• Hands-on experience with LLM production deployment: monitoring, evaluation, and metrics tracking
• Familiarity with on-device ML and performance optimization
• Swift knowledge or interest, as the company’s products operate in the Apple ecosystem
• Background in computer vision, time series, or reinforcement learning

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.

N-iX is looking for a Senior Machine Learning Engineer in Kyiv. You will be responsible for designing, developing, and deploying machine learning models at scale within the Palantir Foundry ecosystem. You will collaborate closely with data scientists, MLOps engineers, and data engineers to build robust, production-grade ML workflows—from data preparation and feature engineering to model training, evaluation, deployment, and monitoring.

Company provides military reservation (after successfully passing trial period).
 

Key Responsibilities

• Design and implement scalable ML models for use in predictive analytics, forecasting, and classification tasks.
• Work with Palantir Foundry to build end-to-end ML pipelines, including custom Python code, Foundry Functions, and Ontology-aware feature generation.
• Collaborate with Data Engineers to ensure high-quality, model-ready data flows from ingestion to inference.
• Operationalize models using industry best practices for versioning, reproducibility, and monitoring (e.g., via MLflow or native Foundry tools).
• Contribute to MLOps automation, including CI/CD for ML, drift detection, retraining pipelines, and evaluation dashboards.
• Partner with business stakeholders and domain experts to translate scientific or commercial hypotheses into model-based solutions.
• Apply rigorous experimentation and statistical validation to ensure models are explainable, generalizable, and regulatory-compliant.
• Stay informed on the latest developments in ML/AI and proactively introduce innovative techniques and frameworks.

Must-Have Skills & Experience

• 3+ years of experience in machine learning or applied data science, ideally in a production or enterprise setting.
• Strong programming skills in Python, with deep experience in machine learning libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Experience designing and deploying ML workflows at scale, preferably with experience in Foundry, KubeFlow, SageMaker, or similar platforms.
• Familiarity with feature engineering, data imputation, sampling strategies, and evaluation techniques 
• Hands-on experience with model deployment and monitoring, including logging metrics, detecting drift, and managing model lifecycles.
• Comfort working with structured and unstructured data: tabular, time series, text, etc.
• Solid understanding of data security, privacy, and compliance.
• Strong communication and stakeholder engagement skills; capable of explaining complex models in simple terms.
• English level at least Upper-Intermediate. 
   

Will be a plus: 

• Experience with Palantir Foundry.
   

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

About the Role We are looking for a Senior MLOps Architect to lead high-stakes AI and Data projects for our enterprise customers. In this role, you will act as the technical authority, helping clients bridge the gap between experimental data science and production-grade operations primarily on Google Cloud Platform. You will lead projects that involve building end-to-end MLOps pipelines from scratch, migrating workloads to Vertex AI, and standardizing model deployment. You will usually act as the "trusted advisor" owning the architecture and the delivery. 

Key Responsibilities 

● Customer Leadership: Lead technical kickoffs, discovery workshops, and architecture reviews directly with client CTOs, VP R&D, and Data Science leads. 

● Architecture & Design: Design robust, scalable MLOps architectures using Google Cloud Platform services (Vertex AI, GKE, BigQuery, Cloud Build, Cloud Storage). 

● Implementation & Automation: Build "Golden Paths" for model deployment. Implement CI/CD pipelines for ML, automated retraining workflows, and model monitoring systems to allow Data Scientists to deploy self-sufficiently. 

● Production Engineering: Operationalize ML models in high-scale environments. Troubleshoot complex infrastructure issues (e.g., GPU provisioning, container orchestration, scaling strategies). 

● Strategic Advisory: Advise customers on best practices for MLOps maturity, cost optimization (FinOps for AI), and data governance. Requirements (Must Have) 

● MLOps Experience: At least 3+ years specialized in MLOps and building production ML pipelines. 

● Google Cloud Expert: Deep, hands-on experience with GCP core services (Compute Engine, GKE, IAM, Networking) and specifically Vertex AI (Pipelines, Feature Store, Model Registry).

● Customer-Facing Skills: Proven ability to lead projects, manage stakeholders, and explain complex technical concepts to clients. 

● Containerization & Orchestration: Strong proficiency with Docker and Kubernetes (GKE). 

● Coding: Strong proficiency in Python and SQL. 

● CI/CD for ML: Experience implementing pipelines using tools like Cloud Build, GitHub Actions, or Jenkins. Big Advantage (Nice to Have) ● Databricks Expertise: Experience with the Databricks Lakehouse platform, Unity Catalog, and MLflow is a major plus. Many of our clients use Databricks alongside GCP, so this skill will be highly valued. 

● Certifications: Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect. 

● GenAI Experience: Experience deploying Large Language Models (LLMs) or working with Gemini/Claude APIs in production.

About the Company

Our client is an early-stage B2B SaaS company building intelligent automation software for finance teams. The platform focuses on real-time financial visibility, automated data ingestion, and advanced cost modeling using modern AI techniques.

The company operates in a large and fast-growing market, with strong early customer validation and active design partners. The team is small, product-driven, and focused on building high-quality software for customers who expect robust, enterprise-grade solutions. This role offers meaningful ownership over core systems and the opportunity to shape foundational technology from the ground up.

About the Role

The company is seeking an AI & Data Engineer to develop the intelligence layer of its platform. In this role, you will design and implement systems that transform messy, heterogeneous business data - such as emails, documents, and spreadsheets - into structured financial models.

You’ll work largely from first principles, deploying services to AWS and operating with a strong MVP mindset: prioritizing simple, effective solutions that can be shipped quickly and iterated on. You’ll collaborate closely with a SaaS engineering team to surface extracted insights through a client-facing dashboard.

Strong engineering fundamentals are expected, including version control, testing, CI/CD, and the ability to break complex problems into small, testable increments while communicating clearly with the team.

Responsibilities:

• Build and maintain ETL pipelines for collecting, cleaning, and structuring customer data;
• Implement document ingestion and vectorization workflows
• Apply NLP and LLM-based approaches to extract structured insights from unstructured data;
• Develop unsupervised models to infer financial structures, cost drivers, and relationships;
• Design custom algorithms to align extracted data with organizational hierarchies and financial models;
• Collaborate with frontend and product engineers to present insights in a clear, intuitive way;
• Maintain strong engineering practices around testing, version control, automation, and documentation;

• Optionally contribute to AWS deployments, infrastructure orchestration, and service integration.

   

Required Skills & Experience

• Hands-on experience with embeddings and vector databases;
• Strong background working with NLP models and large language models (local inference and/or APIs);
• Proven experience building data pipelines and data processing workflows;
• Research-oriented mindset with the ability to design custom solutions beyond off-the-shelf tools;
• Experience deploying and operating systems on AWS;
• Familiarity with automation or data acquisition tools (e.g., workflow automation, scraping, integrations);
• Ability to work independently, iterate quickly, and manage ambiguity;
• Clear communicator who can reason through technical trade-offs;

• Flexibility in working hours when needed.

   

Nice to Have

• Experience applying AI to finance, analytics, or enterprise data problems;
• Broader cloud or infrastructure experience;
• Familiarity with event-driven systems or microservice architectures;

• Background in unsupervised learning on large, messy, real-world datasets.

   

  We Offer: 

• Competitive market salary. 
• Fully remote work. 
• Convenient and somewhat flexible working hours. 
• 28 days of paid time off per calendar year. 
• The chance to work on meaningful, socially valuable products alongside a highly professional, US-based international team. Interesting technical challenges with opportunities to grow and learn.

We are seeking a hands-on Power Apps & AI Engineer to design, build, and operationalize business applications and AI solutions across the Microsoft ecosystem. You will lead end-to-end delivery from discovery and architecture through development, testing, security/governance, and lifecycle management, while partnering with business stakeholders, data teams, and platform administrators. The ideal candidate blends deep Power Platform expertise (Power Apps, Power Automate, Dataverse, Power BI) with modern AI capabilities (Copilot Studio, Azure OpenAI Service, Azure AI Search, AI Builder, Cognitive Services) and can scale solutions using robust environment strategies, DevOps, and compliance controls.

Responsibilities:

Solution Design & Delivery

• Translate requirements into secure, scalable solutions using Power Apps (Canvas & Model-Driven), Power Automate, Dataverse, and Power BI
• Design AI experiences using Copilot Studio (custom copilots), Azure OpenAI Service (prompt design, tool/function calling), Azure AI Search (RAG), AI Builder, and Cognitive Services
• Develop data models, forms, business rules, role-based security, and responsive UX aligned to accessibility standards
• Create custom connectors and leverage the On-Prem Data Gateway for hybrid integrations

AI Engineering & MLOps

• Build RAG pipelines: content ingestion, chunking, embeddings, indexing, grounding, and safety filters
• Operationalize prompt orchestration: context windows, system/user prompts, tool use, fallbacks, and guardrails
• Establish evaluation frameworks: answer quality, relevance, bias/toxicity, and drift monitoring with telemetry
• Partner with data teams to leverage curated datasets, feature stores, and, where applicable, Azure ML for model training and deployment

Required Qualifications

• 4+ years delivering enterprise solutions on Microsoft Power Platform (Power Apps, Power Automate, Power BI, and Dataverse)
• Hands-on experience integrating AI into business workflows using Copilot Studio, Azure OpenAI Service, Azure AI Search, and/or AI Builder
• Proficiency in Power Fx, solution packaging, environment strategies, DLP policies, security roles, and Dataverse schema design
• Practical knowledge of CI/CD with Azure DevOps or GitHub Actions for Power Platform ALM (managed solutions, pipelines)
• Experience building custom connectors; integrating with REST APIs, OAuth2; and using the On-Prem Data Gateway
• Familiarity with Responsible AI principles (safety, privacy, fairness), evaluation metrics, and prompt engineering techniques
• Strong stakeholder engagement, communication, and ability to translate complex requirements into clear technical designs.

What we offer:

• Annual paid leave 18 working days
• Annual paid sick leave
• Opportunity to participate in various events (educational programs, seminars, training sessions)
• English courses
• Healthcare program
• IT Cluster membership
• Competitive compensation

About the project

You will be joining an organisation that builds decision-support systems used in environments where reliability and precision are non-negotiable. Their work combines advanced modelling, simulation, optimisation, and machine learning to help organisations operate with confidence under uncertainty. These systems support complex, operationally critical processes where the consequences of good or bad decisions may play out over months or years.

The team you’ll work with consists of individuals with deep experience in engineering, data science, and analytical problem-solving. They operate in high-stakes contexts where clarity, mathematical rigour, and operational awareness matter. Their focus is on building technology that works in the real world — systems that must stand up to ambiguity, incomplete information, and complex constraints.

As a Forward Deployed Engineer, you will be embedded directly into these environments. You’ll sit between engineering teams and domain experts, helping shape solutions, validate ideas, and build the technical bridges that make advanced decision engines work in messy, real-world scenarios.

About the role

As a Forward Deployed Engineer, you will own the technical execution of projects on the ground. When the platform meets real-world complexity, you will be the one who identifies solutions, implements prototypes, builds integrations, and turns abstract models into production-ready components.

You’ll bridge engineering, modelling, and stakeholder needs - helping turn uncertainty into structure, ideas into working systems, and high-level requirements into technical reality.

What you’ll actually do

• Discover opportunities and frame technical problems in complex operational environments.
• Translate ambiguous business requirements into technical specifications and modelling approaches.
• Lead technical conversations with key stakeholders, domain experts, and engineering teams.
• Design and execute proof-of-concepts that demonstrate measurable progress.
• Build bespoke integrations and data pipelines that connect decision engines to client systems.
• Work hands-on with simulation, optimisation, or ML components to customise solutions.
• Contribute to productionisation efforts, working closely with core engineering teams.
• Bridge communication between engineering, modelling, and operational stakeholders.

• Bring structure, clarity, and momentum to high-pressure, fast-changing situations.

   

About you

• You don’t shy away from operational complexity or ambiguous problem spaces.
• You excel at turning real-world challenges into technical models and working systems.
• You have strong foundations in a quantitative field (e.g., Math, Physics, Computer Science, Engineering, Economics, or similar).
• You’re comfortable writing pragmatic, production-aware code (Python experience preferred).
• You understand the difference between experiments, prototypes, and production systems — and can operate effectively at each stage.
• You enjoy working directly with stakeholders, guiding conversations, and making technical ideas accessible to non-technical audiences.
• You’re curious about decision-making, optimisation, simulation, or ML — and motivated to apply these methods to messy real-world problems.
• You can work independently, analyse constraints, propose solutions, and execute quickly.

• You are very good in English and comfortable communicating with senior stakeholders.

   

What you’ll gain

• Real impact: Your work will shape systems that support critical, high-stakes operational decisions.
• Technical growth: Exposure to state-of-the-art optimisation, simulation, and ML techniques.
• Learning: Direct access to senior engineers and technical leaders with deep experience in complex environments.
• Visibility: Meaningful responsibility from day one — including technical decisions and stakeholder interaction.
• Compensation: Competitive salary based on experience.

Working conditions

• Remote role
• Full-time
• Work schedule: 5 days a week, Saturday and Sunday — days off
• Flexible work schedule and autonomy in planning your time
• All payments are made in euros
• An open sole proprietorship or the ability to open one is required
• Paid vacation and sick leave

Job Description

Technical Skills:

• Proficiency in Python for ML development; familiarity with additional languages like Clojure is a plus.
• Expertise in cloud platforms (AWS, GCP) and data warehouses like Snowflake or BigQuery.
• Strong knowledge of MLOps frameworks (e.g., Kubeflow, MLflow) and DevOps tools (e.g., Jenkins, GitLab, Flux)
• Experience with containerization (Docker) and orchestration (Kubernetes)
• Experience with infrastructure-as-code tools like Terraform

Machine Learning Knowledge:

• Solid understanding of machine learning principles, including model evaluation, explainability, and retraining workflows.
• Hands-on experience with ML frameworks such as TensorFlow or PyTorch

Big Data Handling:

• Proficiency in SQL/NoSQL databases and distributed computing systems like Dataprov, EMR, Spark, Hadoop

Soft Skills:

• Strong communication skills to collaborate across multidisciplinary teams.
• Problem-solving mindset with the ability to work in agile environments

Experience:

• At least 5+ years in platform, software, or MLOps engineering roles
• Proven track record of deploying scalable ML solutions in production environments

Job Responsibilities

Model Deployment and Operations:

• Deploy, monitor, and maintain machine learning models in production environments.
• Automate model training, retraining, versioning, and governance processes.
• Monitor model performance, detect drift, and ensure scalability and reliability of ML workflows

Infrastructure and Pipeline Management:

• Design and implement scalable MLOps pipelines for data ingestion, transformation, and model deployment.
• Build infrastructure-as-code solutions using tools like Terraform to manage cloud environments (AWS, GCP)

Collaboration with Teams:

• Work closely with data scientists to operationalize machine learning models.
• Collaborate with software engineers to integrate ML systems into broader platforms

Cloud and Big Data Expertise:

• Utilize cloud services from AWS, GCP, and Snowflake for scalable data storage and processing.

DevOps Integration:

• Implement CI/CD pipelines and automations to streamline ML model deployment.
• Use containerization tools like Docker and orchestration platforms like Kubernetes for scalable deployments
• Use Observability platforms to monitor pipeline and operational health of model production, delivery and execution

Department/Project Description

Our team consists of 100+ engineers, designers, data scientists, implementation, and product people, working in small inter-disciplinary teams closely with creative agencies, media agencies, and with our customers, to develop and scale our leading digital advertising optimization suite that delivers amazing outcomes for brands and audiences.

Our platforms are built with Python, React, and Clojure, are deployed using CI/CD, heavily exploit automation, and run on AWS, GCP, k8s, Snowflake, BigQuery, and more. We serve 9 petabytes and 77 billion objects annually, optimize thousands of campaigns to maximise ROI, and deliver 20 billion ad impressions across the globe. You’ll play a leading role in significantly scaling this further.

As our first Machine Learning Operations (MLOps) Engineer, you will play a pivotal role in bridging the gap between platform engineering, data science, and software engineering, building systems that drive the deployment, monitoring, and scalability of machine learning models. You will design and implement pipelines, automate workflows, and optimise model performance in training and production environments. You’ll lead the creation of process, implementation of tools, and creation of solutions mature how we integrate machine learning solutions into our production systems, while maintaining reliability, security, and efficiency. You’ll additionally play a leading role in driving continuous improvement in model lifecycle management, from development to deployment and monitoring.

RESPONSIBILITIES 

• Work closely with sales, delivery, and expert teams to align client needs with data-driven solutions, effectively connecting business challenges to our offerings
• Own the end-to-end presales process, including opportunity qualification, solution design, proposal development, demos, and client presentations
• Lead workshops and meetings with clients to gather business objectives and technical requirements, ensuring alignment between client goals and our solutions
• Architect tailored data solutions, encompassing cloud-native platforms, data integration, advanced analytics, and AI/ML models, to provide actionable business insights
• Develop competitive proposals, pricing models, and value propositions to successfully close opportunities and secure engagements
• Stay updated on emerging trends in Data & Analytics, Cloud, and AI, providing strategic advice to clients and supporting innovation within the practice
• Contribute to the development of reusable solution frameworks, accelerators, and methodologies to drive operational efficiency
• Act as a mentor and knowledge-sharer across the team, supporting skill-building and best practice dissemination.

QUALIFICATIONS  

• Extensive experience in presales, solution architecture, or consulting, with a focus on Data/AI technologies and related business use cases
• Strong technical knowledge of data platforms (e.g., Databricks, Snowflake, AWS/Azure/GCP Data Services), ETL processes, data modeling, BI tools, and data visualization frameworks (e.g., Power BI, Tableau)
• Familiarity with data science techniques and proficiency in analyzing client needs to align with technical solutions
• Excellent communication and storytelling skills—able to translate complex technical concepts into clear, client-friendly narratives
• Proven track record in engaging with senior stakeholders and delivering impactful presentations or pitches
• Experience in creating detailed proposals, RFP responses, and pricing/engagement models for data-related services or projects
• Understanding of strategic consulting principles and the ability to develop future-state recommendations and roadmaps for client success
• Strong organizational, leadership, and project scoping abilities, with a proven ability to manage complex tasks in a fast-paced environment
• Bachelor's or master's degree in data science, Computer Science, Business Analytics, or a related field (or equivalent professional experience)
• Excellent English communication skills, with the ability to clearly and effectively explain technical concepts to diverse audiences.

#WeAreIn for jobs that impact everyone's life. What if your ideas could change the way the world connects, powers up, or thinks? As a Senior AI/ML Engineer on our Research & Development team, you'll have the opportunity to merge creativity with your technical expertise by shaping the future of technology, driving groundbreaking projects, and bringing new ideas to life. Are you in?

Key responsibilities in your new role

Work on innovative IoT, Industrial, and Automotive technologies in a fast-moving R&D team, turning ideas into real products and patents. 

• Design and develop efficient Neural Network (NN) models with sophisticated architectures for embedded domain, strongly involving application-specific knowledge
• Plan and execute practical experiments to collect/create high-quality datasets
• Combine NN and classic signal processing approaches to make the highly efficient pipelines of problem solving
• Implement the developed solutions under real-world end-user scenarios and requirements and verify its functionality at the Infineon hardware (PSOC, wireless SOCs)
• Help with ML/AI related design and implementation in different team projects

Your Profile

Qualifications and skills to help you succeed

• A master’s degree in electrical engineering or computer science (or equivalent) and 2-3 years of related research/engineering experience
• Strong background in mathematical modeling and numerical analysis
• Knowledge of modern NN architectures, Machine Learning tools and trends
• Proficiency in Python and at least one ML framework (PyTorch or TensorFlow)
• Experience with at least one of the following: signal / speech /image / video processing / wireless communication is a plus
• Understanding of embedded systems and Knowledge of Nvidia Deep Learning framework, and familiarity with patents, papers, publications on relevant technical subject matter is a plus
• Intermediate English writing, communication, and presentation skills

Please send us your CV in English.

An AI-powered concierge system that transforms hotel guest services through specialized AI agents working together to handle bookings, recommendations, travel planning, and customer support - all through natural conversation.

Required experience:
- 2+ years with AWS Bedrock, Azure Foundry, LangGraph, n8n, or similar enterprise GenAI & multi-agent orchestration frameworks (including Agent-to-Agent communication protocols)
- 2+ years with LLMs in production (Claude, GPT-4/5, Gemini)
- 5+ years of backend and frontend development (NodeJS, TypeScript, React)
- 2+ years with Supabase and PostgreSQL (including Supabase serverless Edge Functions)

Supplementary Skills (a big plus):
- Payment integrations (Stripe)
- Map APIs (Mapbox)
- Multi-language AI systems
- Hospitality/travel industry knowledge

Responsibilities:
- Develop a production-ready MVP based on existing prototypes
- Design and implement specialized AI agents (booking, concierge, travel) and their orchestration
- Optimize LLM prompts and response quality
- Monitor performance and control AI costs
- Implement safety validation and error recovery
- Manage API integrations (Stripe, Mapbox, document parsing)

Bond Studio makes software that lets users capture their space with their phone and see a visualization of how that room could look if it were remodeled.  Users can browse products, select them, and see them visualized in their space.  

Part of this experience is search where users can type in queries and see products based on their query.  Currently this functionality is powered by a custom Python service that contains an index of all of our products and leverages LLMs to provide results to users.
Search quality and speed are critical to the overall user experience.
We have a comprehensive benchmark for this service and are looking to work with a software engineer to improve its performance on this benchmark.

This is not a greenfield project. You will be working with an existing production system and are expected to diagnose bottlenecks, propose improvements, and implement measurable gains.

You will analyze and improve a real-world product search system that includes:

A large, structured product catalog with many attributes and variants.
User-driven filtering and refinement (dimensions, style, finish, price, etc.).

Natural-language queries interpreted by an LLM-backed layer.
 

A backend search service that must be fast, stable, and scalable.
 

The focus of this engagement is on result quality while maintaining acceptable performance.