Top Machine Learning Jobs in Warsaw

Lead software engineering efforts for Samsara’s External Platform EMEA, building scalable distributed systems, APIs, reporting, administration, integrations, and business-critical infrastructure. Lead technical discussions, influence architecture and roadmap, deliver full-stack features, maintain production systems, and support customer-focused iteration. Mentor engineers, hire and develop high-performing teams, and contribute to machine learning-powered products and long-running projects.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Leads analytical methodology and evaluation for AI-based healthcare and pharmaceutical workflows. Owns model selection, cohort and HCP segmentation, agent decision logic, and evaluation frameworks. Partners with engineering, data architecture, and governance teams to productionize rigorous analytical methods, identify new data and techniques, communicate insights, and mentor data science and engineering colleagues.

Leads data science methodology and advanced analytics for AI-enabled Medical Affairs workflows. Develops and evaluates statistical, machine-learning, NLP, and AI models using healthcare and real-world data; defines validation, monitoring, and decision frameworks; partners with engineering, governance, and business teams to operationalize solutions. Provides technical leadership, mentorship, documentation standards, and strategic guidance while ensuring privacy, compliance, responsible AI use, and clear communication of analytical findings.

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Designs, develops, evaluates, and deploys AI, machine learning, GenAI, and agentic AI solutions. Translates business needs into scalable production capabilities using LLMs, RAG, semantic search, enterprise data, APIs, and intelligent workflows. Partners with business, analytics, and technology teams to move proofs of concept into reusable solutions while applying software engineering, MLOps, LLMOps, security, governance, monitoring, and documentation best practices.

Designs, builds, and operates production AI workflows integrating HR, Finance, Operations, and CRM systems. Responsibilities include orchestration, AI agents, prompt engineering, retrieval pipelines, model evaluation, monitoring, feedback loops, and decision-quality improvement. The role partners with Data Engineering on infrastructure, CI/CD, data pipelines, security, governance, and shared AI standards while tracking outcomes such as accuracy, resolution rate, and time saved.

Support development and fine-tuning of ML and Agentic AI solutions for pharma/healthcare. Assist in building, testing, and validating prototypes and production-grade algorithms using large real-world datasets. Collaborate with ML engineers, researchers, and clients to deliver deployable AI products.

Perform multilingual legal data collection, evaluation, and annotation for AI-powered contract management platforms. Analyze clauses, obligations, and terms in international business agreements, participate in onboarding and calibration sessions, conduct quality reviews, and collaborate within secure client environments. Requires legal or contract expertise and fluency in English and Polish. Prior data annotation or machine learning evaluation experience is preferred.

Manage relationships with AI-native startups, scaleups, and research labs; understand their technical and business needs; develop high-value NVIDIA solutions; drive adoption of AI platforms; coordinate with solution architects, engineering, business development, and go-to-market teams; cultivate ecosystem partnerships, customer references, case studies, and emerging use cases; and represent NVIDIA at industry events.

Designs and deploys production AI/ML solutions and agentic workflows, translating ambiguous business problems into modeling approaches. Builds GenAI evaluation frameworks, golden datasets, testing harnesses, and MLOps/LLMOps pipelines with observability. Implements governance, security, fairness, privacy, and explainability controls while partnering with product, engineering, and business stakeholders on AI adoption, impact, and cost optimization.

Own the vision, roadmap, backlog, and delivery of AI-powered products. Translate business challenges into scalable solutions, define KPIs and business cases, prioritize initiatives, manage stakeholders, drive adoption, and measure business impact. Collaborate with AI engineers, data teams, IT, security, and governance stakeholders to develop reusable AI capabilities across markets and functions.

Own the full sales cycle for AI compute services, including GPU infrastructure, managed inference, and serverless solutions. Build pipeline, qualify workloads, design solutions with architects, manage enterprise and public-sector sales, lead RFPs and pilots, close complex technical deals, and expand accounts. Develop partner relationships, forecast revenue, maintain CRM discipline, represent the company at events, and provide customer feedback to product and operations teams.

Develop and refine machine learning and LLM-based solutions, including agent architectures, embeddings, clustering, summarization, and automated workflows. Design experiments and metrics to evaluate model quality, build Java and Python services hosted on Snowflake and Kubernetes, troubleshoot systems, and collaborate with product, design, and partner teams to deliver features and shape product direction.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Leads NN Poland’s AI Enablement Team and Center of Excellence, shaping Data & AI strategy, governance, architecture standards, investment priorities, and an enterprise portfolio of AI initiatives. Evaluates opportunities, drives experimentation and proofs of concept, and enables secure, responsible, production-ready AI adoption. The role manages resources, budgets, capabilities, and cross-functional collaboration across business, technology, security, risk, legal, compliance, and data governance teams.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.

Annotate, label, categorize, and tag image and video data used to train machine learning models for smart robots. Follow detailed instructions, report issues, and assist other teams as needed. The role requires strong English communication, attention to detail, organization, willingness to learn, and a hands-on attitude. It is remote within Poland, offers flexible hours, and involves working in an English-speaking robotics environment.

Build and improve production-oriented AI applications, including agents, RAG pipelines, LLM integrations, and data applications. Develop evaluation frameworks, test datasets, observability, safety guardrails, monitoring, and human-review workflows. Collaborate with AI engineers, researchers, customers, Product, and Engineering teams while writing tested Python and SQL. Participate in software development activities such as design reviews, code reviews, debugging, documentation, deployment, and experimentation.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Leads clinical data science delivery and team development, designing advanced statistical models and machine learning methods for clinical research. Oversees data analysis, management, regulatory compliance, and trial optimization while collaborating with clinical, biostatistical, and regulatory teams. Communicates complex insights to senior stakeholders and external partners and drives innovation across clinical development programs.

Develop and maintain automated backend and API tests, test backend services, analyze results and logs, maintain test plans and documentation, track defects, and collaborate with development and operations teams. The role requires strong Python and Pytest skills, REST and gRPC testing, Linux and Bash, Docker, Kubernetes, CI/CD, SQL, Kafka or Kibana, and familiarity with microservices and machine learning.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.