Top Machine Learning Jobs in Poland

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.

Designs and specifies 5G radio network system features, algorithms, test cases, and use cases, primarily focused on Radio Resource Management. Develops network-level simulations, analyzes performance data, supports system verification and customer troubleshooting, contributes to 5G/6G standardization and patents, and assists with deploying products into live networks. Collaborates with global development, customer, and cross-functional teams.

Develop and improve computer vision systems focused on aerial image recognition for a roofing technology platform. Build, train, evaluate, fine-tune, and deploy models for detection, segmentation, classification, and pattern recognition. Research and prototype modern vision, foundation, multimodal, and language-model solutions; optimize accuracy, reliability, and inference performance; prepare data pipelines; and identify product opportunities for AI. The role requires independent ownership of open-ended technical challenges from research through deployment.

Develop and deploy computer vision and machine learning systems for aerial image recognition in construction technology. Responsibilities include object detection, segmentation, classification, model training and optimization, rapid prototyping, multimodal AI experimentation, data pipeline development, and researching AI applications that improve product functionality and user experience.

Develop and improve computer vision systems focused on aerial image recognition. Build, train, fine-tune, evaluate, and deploy models for detection, segmentation, classification, and pattern recognition. Research modern vision, foundation, multimodal, and language models; rapidly prototype ideas; optimize accuracy and inference performance; create data pipelines; and identify AI opportunities across the product. The role requires ownership of technical challenges from research through implementation.

Own the strategy, roadmap, execution, and business outcomes for MEDvidi’s AI Receptionist product. Lead cross-functional collaboration across Product, Engineering, Clinical, and Operations teams; improve conversational AI quality through experimentation, evaluation, analytics, and user feedback; define success metrics; and ensure safety, privacy, and reliability in regulated healthcare workflows.

Lead the technical vision, design, development, and deployment of AI-powered mobile and edge solutions across Android, iOS, and Windows. Build production-ready machine learning pipelines, AI services, device integrations, observability capabilities, and scalable mobile applications. Mentor engineers and collaborate with product, UX, architecture, and business teams. The role emphasizes IoT, embedded systems, edge AI, generative AI, computer vision, predictive analytics, and regulated-industry applications.

Explore, evaluate, and operationalize emerging AI methodologies, models, architectures, and technologies. Design experiments, benchmarks, evaluations, and proofs of concept; develop and productize generative, agentic, multimodal, and machine learning solutions; translate research into reusable enterprise capabilities; and collaborate with platform, data, product, architecture, and engineering teams to scale AI across Danaher.

Lead a distributed engineering squad building and operating email security products. Own delivery planning, architecture, code and design reviews, production reliability, SLOs, incident response, model quality gates, technical debt, and roadmap development. Coach, hire, and develop engineers while establishing effective remote-work practices. The role combines approximately 60% technical leadership and people management with 40% hands-on engineering, including debugging, production changes, and AI-assisted development practices.

Leads Danaher’s global AI Engineering, Integration and Operations organization, converting AI prototypes and capabilities into secure, scalable, production-grade solutions. Responsibilities include establishing engineering and operational practices, leading multidisciplinary teams, partnering with product and governance leaders, planning engineering capacity, and ensuring reliable deployment, support, adoption, and continuous improvement of enterprise AI solutions.

Own the strategy, roadmap, metrics, and adoption of JetBrains Context, a managed retrieval layer for AI coding agents. Partner with engineering, ML, platform, IDE, marketing, sales, and customer success teams to improve indexing, retrieval quality, integrations, reliability, cost, and latency. Define product direction, evaluate competitors, establish quality metrics, communicate with customers and developer communities, and drive enterprise adoption.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Lead advanced data science projects, develop AI/ML products, build ML-powered web applications, and manage product lifecycle while collaborating across functions.

Develops analytical and machine learning solutions for finance risk and control processes. Responsibilities include data governance, ERP data extraction, reporting, Power BI development, technical environment maintenance, risk analytics, and translating business needs into digital solutions. The role partners with Risk Managers, ERP teams, Process Operations, and Global Process Owners to improve controls, identify process risks, and deliver insights. It requires strong hands-on expertise in Azure, SAP, SQL, Python, data engineering, and financial risk management.

Own the data foundation for Operations, including BigQuery data flows, analytical models, automated KPI dashboards, and Tableau reporting. Analyze payments, support, online reputation, funnels, churn, lifetime value, fraud, and operational bottlenecks. Partner with Operations leaders to convert insights into process improvements and business growth, while implementing AI and LLM automation for support classification, routing, and fraud detection.

Lead data strategy, architecture, governance, quality, compliance, and technology adoption. Translate stakeholder needs into scalable data initiatives, support advanced analytics and AI/ML, promote data literacy, and guide cross-functional teams toward data-driven decision-making.

The FP&A Manager leads financial planning, management reporting, and forecasting processes, providing insights for strategic decision-making alongside senior stakeholders.

Build and operate production AI systems, including LLM agents, multimodal applications, RAG pipelines, classical ML models, and AI services. Own solutions from requirements and prototyping through deployment, monitoring, evaluation, and support. Develop Python services on Azure using PostgreSQL, Terraform, containers, CI/CD, and observability tools. Integrate AI with engineering, manufacturing, testing, and business systems while improving technical architecture, mentoring engineers, and guiding responsible AI adoption.

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.

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.

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.

Optimize the performance of renewable energy assets, particularly battery energy storage systems, through performance analysis, machine learning, forecasting, condition monitoring, and fault prediction. Identify upgrade opportunities, assess technical and commercial viability, investigate lost production and root causes, and advise asset supervisors on technical and performance issues.

Develop and maintain ROS-based robotics solutions for visitor experiences, operations, and educational programs. Responsibilities include perception and navigation software, firmware, hardware calibration, testing, monitoring, deployment maintenance, and collaboration with external partners. The role involves hands-on work with LiDARs, IMUs, Linux environments, and robotics hardware, with opportunities to progress into core software development, AI, and full-stack robotics work.