Jobs ML / AI

​Winstars.AI is a research and development center comprising scientists, engineers, and visionaries dedicated to leveraging advanced technologies to enhance global efficiency and security. 

We are looking for a highly skilled Senior MLOps Specialist with expertise in Python, cloud computing, machine learning, and large-scale data processing.

THAT WOULD BE WONDERFUL IF YOU HAVE:

• Hands-on experience with AWS services such as S3, AWS Batch, EC2, and Lambda for processing large-scale data.
• Experience in building and deploying scalable MLOps pipelines, including model deployment, versioning, and experiment tracking (e.g., using ClearML or similar tools).
• Proficiency in Python, with solid knowledge of libraries and frameworks used for data processing and machine learning.
• Expertise in automating data ingestion and quality control (QC) processes, specifically with medical data formats like DICOM, C-Arm images, and radiology reports.
• Experience in distributed data processing on platforms like AWS Batch (Spot) for large-scale processing and predictions.
• Familiarity with PostgreSQL for storing and managing metadata, and building services for metadata enrichment and prediction results.
• Experience working with regulatory frameworks such as FDA-compliant environments (21 CFR Part 11) and handling HIPAA/PHI data in accordance with industry standards.
• Strong understanding of data governance, access control, and audit trails, especially in clinical and healthcare-related environments.
• Upper-intermediate+ in English;

WOULD BE A PLUS:

• Active Kaggle participation;
• Experience in Computer Vision

About Us 

ChatRevenue.ai was founded by Ratmir Timashev (founder of Veeam) and Vlad Voskresensky (founder of Revenue Grid) to create the next generation of CRM systems. 

We’re building an AI-native CRM platform that completely redefines how sales automation works. 
By structuring data for intelligent automation, we enable agentic AI to design workflows, assist Sales Leaders and Reps in real time, and generate predictable sales funnels – all through a simple, chat-driven interface. 

Our mission: to build a CRM that works for User, not the other way around. 

About the Role 

This role is for engineers who thrive in dynamic environments, where processes are still being shaped and impact is immediate. 

At ChatRevenue, we focus on goals rather than ceremonies – no endless grooming sessions or heavy planning rituals. Decisions are made quickly through open dialogue and collaboration, not through layers of approvals. 

Previous startup experience is not required – what matters is curiosity, independence, and drive. As part of the core team, you’ll have the chance to own technical domains, lead innovation, and grow together with the company. 

What You’ll Do 

• Design, deploy, and maintain GenAI/RAG pipelines for production 
• Integrate LLMs and agentic assistants into business flows 
• Source, ingest, clean, and enrich external data streams 
• Build and manage vector search, embedding stores, and knowledge graphs 
• Explore and implement new ML/GenAI frameworks and multi-agent systems 
• Mentor developers and share knowledge across the team 

What We’re Looking For 

• Strong backend skills: Python, FastAPI, Webhooks, Docker, Kubernetes, Git, CI/CD 
• Hands-on experience with LLMs (OpenAI-family), LangChain/LangGraph/LangSmith, prompt engineering, RAG, vector stores (Azure AI Search, Pinecone, Neo4j, FAISS) 
• SQL, Pandas, Graph DBs (Neo4j), NetworkX, ETL/data cleaning, Kafka/Azure EventHub 
• Proven experience running RAG pipelines in production 
• Familiarity with graph algorithms (community detection, similarity, centrality) 
• Good English for documentation, API design, and teamwork 
• Startup drive, proactivity, independence 
• Willingness to relocate or travel within Europe; full-time availability 

Nice to have 

• Multi-agent LLM frameworks 
• Big Data pipelines in cloud (Azure preferred) 
• Production-grade ML/NLP, Graph ML 

Why Join Us 

• Remote-first culture – work from anywhere 
• Flexible schedule aligned with European time zone 
• Direct impact – your work is visible in the product from day one 
• Professional growth – own technical domains, lead innovation, scale with the company 
• Competitive compensation: $6000-9000 
• Core team – become one of the people who know the product best and shape its future 

If you want to be part of the core team building an AI-native CRM from scratch, we’d love to hear your story. 

N-iX is looking for a Lead Data Scientist. As a Lead Engineer, you’ll be responsible for designing, developing, and optimizing data and AI pipelines (including Spark-based and RAG-style workflows), ensuring performance, scalability, and reliability. You’ll also be working on technical discovery and solution assessment: helping the client understand existing AI tooling (currently a RAG-based solution used for document analysis), evaluating scalability, quality, cost, and risks, and advising on future architecture options.

Responsibilities:

• Design and implement data pipelines to support AI and ML use cases, including data preparation, feature engineering, and real-time model serving.
• Support and enable RAG-based and NLP use cases, including document ingestion, data preparation, feature extraction, and structured data generation.
• Collaborate with AI engineers to productionize AI/ML solutions and integrate them into reliable data workflows.
• Participate in and lead discovery phases to analyze existing AI solutions, clarify how they work, and identify architectural gaps, risks, and improvement opportunities.
• Assess scalability and multilingual support of AI/data solutions (including feasibility, configuration needs, cost, and expected quality).
• Contribute to evaluations of vendor lock-in, platform alternatives, and potential migration paths (e.g., toward Palantir Foundry or other modern data/AI platforms).
• Ensure high standards of data quality, security, governance, and compliance.
• Drive continuous improvement in development processes, tooling, and engineering practices.
• Foster collaboration across engineering, data science, and product/business stakeholders.

Requirements:

• 6+ years of experience in data
• Proficiency in Python and distributed computing concepts.
• Experience designing and optimizing scalable data pipelines for high-volume data.
• Experience supporting AI/ML projects (e.g., enabling model training pipelines, feature engineering, real-time inference, or MLOps workflows).
• Ability to perform technical discovery and solution assessment, including explaining complex systems to non-technical stakeholders.
• Strong leadership, communication, and stakeholder management skills.
• Experience with Palantir Foundry is a plus, but not required.
• Experience with PySpark and large-scale data processing.

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

About the role

We’re looking for an experienced AI Automation & Prompt Engineering Specialist to collaborate with us on a project-based, long-term freelance basis. We’re interested in working with someone who knows how to combine large language models with automation, data extraction, and structured outputs to solve real business problems.

This role is not about writing standalone prompts. It is about designing reliable, repeatable AI-assisted processes that integrate LLMs with data sources, automation tools, and validation logic.

You’ll work with us on a project basis, joining specific initiatives over time, with recurring tasks and room to expand the scope as we continue working together.

What you will work on

• Designing prompt chains and AI-assisted workflows for research, sales intelligence, and data enrichment tasks
• Building AI-driven pipelines that combine LLM reasoning with data extraction, normalization, and validation
• Defining structured outputs (tables, spreadsheets, datasets) suitable for sales and research teams
• Improving accuracy and reliability of AI-generated outputs through validation logic and iteration
• Documenting workflows and approaches so they can be reused and scaled internally
   

Required skills and experience

AI & LLM expertise

• Strong practical experience working with large language models (ChatGPT, GPT-based APIs, or similar)
• Clear understanding of LLM capabilities and limitations (generation vs extraction vs classification)
• Experience designing multi-step prompt chains rather than single prompts
   

Automation & data handling

• Experience with automation tools and approaches such as:
  • Browser automation or scraping concepts (e.g. Playwright, Puppeteer, Selenium, or equivalents)
  • No-code / low-code tools (Make, Zapier, Apify, Phantombuster, or similar)
• Ability to work with structured data (Excel, Google Sheets, CSVs)
• Understanding of data normalization, deduplication, and basic validation
   

Technical mindset

• Comfortable working with technical constraints (logins, rate limits, inconsistent data sources)
• Ability to propose realistic solutions, not “AI magic”
• Basic scripting or coding knowledge (Python or similar) is a strong advantage
   

Professional requirements

• Previous relevant experience that can be demonstrated through case studies or examples of past work
• Availability for ongoing freelance work on a project basis
• Registered as a self-employed specialist / sole trader (or equivalent)
• Good working proficiency in English (written and spoken)
• Ability to work independently and communicate clearly with non-technical stakeholders
   

Nice to have

• Experience in B2B, sales operations, research, or growth teams
• Familiarity with media, technology, or digital platforms industries
   

What we offer

• Project-based tasks with clear scopes and deadlines
• Flexible workload depending on active projects
• Interesting, non-trivial AI use cases focused on real business outcomes
• Freedom to propose better tools and design approaches and an opportunity to test out your ideas
• Build public case studies through projects with a UK-based technology company, highlighting international experience
• Receive professional references to support future roles or client engagements

# ai researcher in metalearning 

- client: ai product development company from germany
- product: cogit - ai agent-based automation platform
- experience: machine learning, self-optimization systems, prompt engineering, llm evaluation
- tasks:
   - architect the agent.maker meta-framework with sub-agents (instruction.maker, config.maker, screen.maker)
   - develop self-improvement loops for iterative prompt refinement
   - build evaluation framework for agent output quality (instructions.md, config.yaml generation)
   - implement llm observability and tracing (phoenix/arize integration)
   - create quality metrics for generated agents (tool usage accuracy, task completion rate)
   - develop prompt mutation strategies based on execution feedback
   - build fitness evaluation for config parameters (model selection, temperature tuning)
   - implement learning mechanisms from agent execution logs
   - create benchmarks comparing models (gemini vs claude) for different agent tasks
- languages: python
- libraries: google adk, anthropic sdk, phoenix tracing, pydantic, yaml

AI Engineer / Data Analyst (Social Media Analytics)

We are looking for a technical specialist to improve and develop a product focused on collecting, processing, and analyzing comments from social media platforms.
 

Responsibilities:

• Develop and improve tools for automated data and comment collection
• Build AI/ML solutions for:
  • text and comment analysis
  • sentiment detection, topic extraction, pattern recognition
  • structuring and processing large datasets
• Work with numbers, metrics, and analytical outputs
• Create custom tools and solutions based on specific product and business needs
• Optimize and automate data collection and analysis pipelines
   

Requirements:

• Experience with AI / ML and building automation solutions
• Strong background in data analysis and working with large datasets
• Experience in developing custom tools for product-oriented tasks
• Understanding of data collection, storage, and processing principles
   

Nice to Have:

• Experience working with social media platforms:
  • TikTok
  • Instagram
  • YouTube
  • Facebook
  • Threads
  • Snapchat
  • Twitter (X)
  • Telegram
• Experience with social media APIs or data scraping
• Knowledge of NLP techniques (sentiment analysis, topic modeling, text classification)
• Understanding of user-generated content (UGC) and comment behavior

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.

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)

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.

New long-term project for an Energy client, where we will create an application for intelligent alarms processing to support various users with their operational activities. You will be part of a big team, where we’ll have C# engineers, AQAs, POs, DevOps and Project Managers.

Requirements: 

• 4+ Experience software development at an enterprise scale
• 3+ years of experience in applied ML in the industry with a degree in computer science, machine learning, mathematics or similar field
• Strong knowledge (3+ years experience) of Python programming languages building production systems
• Demonstratable experience building and deploying highly scalable systems, algorithms, and tools on platforms to support machine learning and deep learning solutions
• 1+ year experience with big data systems like Spark, Hadoop, Hive, Databricks, or other large scale data processing engines
• Graduate Degree (MS or PhD) in Statistics, Computer Science, Physics, Applied Mathematics or Mathematics from an accredited university
• Good English to work with clients directly

Responsibilities: 

• Strong problem-solving and follow-up skills; must be proactive and take initiative
• Professionalism and ability to maintain the highest level of confidentiality
• Create robust code and translate business logic into project requirements
• Develop code using development best practices, and an emphasis on security best practices
• Leverage technologies to support business needs to attain high reusability and maintainability of current and newly developed systems
• Provide system design recommendations based on technical requirements
• Work independently on development tasks with a minimal amount of supervision
• Write effective unit tests and integration tests to ensure high-quality software delivery
• Support Lead, Scrum Master and PO

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

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

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 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.

About Genius Match 

Genius Match was established in 2008 with the mission to connect exceptional global technical talent with high-growth opportunities. We have served as strategic partners to leading technology companies, innovative startups, and established enterprises by building cohesive, high-performing engineering teams that deliver immediate impact.  

Since our inception, our long-standing commitment to excellence has driven our exceptional client retention rate and our ability to truly understand our clients' business goals, speak their technical language, and consistently deliver both immediate value and long-term results. In the same way that we strive to support our clients and employees, we’re passionate about making a positive difference in our global community. 

The Opportunity 

We are seeking an experienced Staff AI/ML Engineer to lead the design and deployment of advanced AI solutions across a range of applications. You will focus on AI system architecture, generative AI, LLM integration, and enterprise-grade AI application development. The ideal candidate combines deep technical expertise with leadership skills to guide teams, establish best practices, and deliver innovative AI solutions that scale. 

As an AI Engineer, you will:

•  

   

  Design, develop, and deploy AI and machine learning models, including generative AI and NLP applications;

   

   

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  Work with LLMs, AI agents, RAG, and prompt engineering to build AI-powered solutions;

   

   

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  Apply machine learning and deep learning techniques for text analysis, classification, extraction, and other data-driven tasks;

   

   

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  Collaborate closely with product and engineering teams to translate business problems into technical solutions;

   

   

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  Contribute to prototypes, new product features, and enhancements for existing products. 

   

   

Qualifications: 

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  3+ years of software development experience with at least 2 years in machine learning, NLP, generative AI, or related fields;

   

   

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  Hands-on experience with LLMs and AI techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation;

   

   

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  Strong programming skills in Python, with experience using ML libraries such as PyTorch, Huggingface Transformers, Scikit-learn, SpaCy, or similar;

   

   

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  Experience with SQL/NoSQL databases and cloud platforms;

   

   

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  Solid understanding of ML algorithms, statistical modeling, and deep learning;

   

   

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  Experience deploying ML or AI models into production environments;

   

   

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  Comfortable working in agile, collaborative teams in a remote or distributed setup;

   

   

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  MS, PhD, or equivalent experience in Computer Science, Data Science, or related fields. 

   

   

What we offer: 

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  Competitive market compensation; 

   

   

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  Fully remote work with flexible hours;

   

   

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  Work on socially impactful products with a US-based, international, high-performing teams;

   

   

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  Opportunity to tackle complex challenges, grow professionally, and influence product direction. 

   

   

We are looking for an experienced ML Engineer (5+ years of commercial experience) to join a fast-growing AI product focused on building and scaling AI-powered logistics solutions for the US market. (FREELANCE POSITION)

You will work on designing, developing, and maintaining data pipelines and machine learning infrastructure that power autonomous digital workers and enable data-driven decision-making across the organization.

About the project:

The project is committed to helping businesses efficiently scale their supply chains, regardless of size, stage, or industry.
Their mission is to empower organizations through practical, scalable AI solutions that drive real operational impact.

What you will do:

• Collaborate closely with engineering, analytics, data science, and product teams
• Contribute to existing ML projects from day one
• Design, build, and maintain data pipelines required for ML solutions
• Own the data and ML processes you create end to end
• Become a domain expert in the company’s ML and data infrastructure, influencing key technical decisions

• Work on cutting-edge projects at the intersection of GenAI, ML, and data science within the logistics domain

   

Tech stack:

• Python
• SQL, dbt
• AWS
• ETL / data pipelines
• LangChain, LangGraph, LangSmith
• Modern ML tooling
• Data integrity, monitoring, and quality assurance

What we’re looking for

• 5+ years of commercial experience in Machine Learning / Data / Analytics Engineering
• Experience designing and deploying ML models in AWS
• Strong understanding of the full ML product lifecycle
• Proven experience implementing data engineering best practices (ETL, data integrity, monitoring)
• Solid hands-on experience with Python, SQL, and dbt
• Experience refactoring large-scale data models for performance, interpretability, and maintainability
• Experience with agentic pipelines and tooling (LangChain, LangGraph, LangSmith)
• Experience with Git (GitHub / GitLab) and Agile methodologies
• Strong communication skills and ability to collaborate across teams
• Strong English (comfortable 1:1 calls, proactive communication)

• Bachelor’s degree in a quantitative field (Computer Science, Engineering, Physics, etc.) or equivalent practical experience

   

Engagement details

• Full-time
• Long-term engagement (6+ months)
• Client location: USA
• Citizenship requirement: Ukrainian

Interview process

1. Recruiter interview
2. Internal technical interview
3. Client interview