Top Machine Learning Jobs in Poland

The Fund Accounting Supervisor oversees cash and position reconciliations, reviews fund pricing and compliance, mentors team members, and ensures deadlines are met.

The FP&A Group Reporting Manager leads group-level financial reporting, analysis, and strategic decision support for the CFO and Executive Board, ensuring accuracy and driving continuous improvement in financial insights.

The ORR Technology Lead Analyst executes testing activities for risk assessments, collaborates with business lines, identifies control weaknesses, and prepares documentation on compliance and operational risks.

As a Senior ML Researcher at JetBrains, you will train LLMs for software engineering agents, design experiments, and mentor junior colleagues.

The Senior Machine Learning Engineer will design and implement ML pipelines, optimize LLM performance, and collaborate on AI infrastructure for cost-efficient solutions.

Lead and architect Nearmap's ML platform, guiding the team in developing robust systems and implementing best practices for MLOps and AIOps.

The Senior Machine Learning Engineer will execute software engineering tasks for machine learning operations, design MLOps systems, mentor team members, and ensure reliable ML systems using modern technologies.

The Senior Manager of Logistics Operations will oversee Moderna's European logistics hub, ensuring compliance, efficiency, and integration of advanced technologies while managing day-to-day logistics operations.

The role involves developing machine learning systems for robotic applications, enhancing robot dexterity, and collaborating on innovative solutions. It requires strong problem-solving skills and experience with deep learning and computer vision.

Design and develop software solutions for AI/ML applications, propose new approaches to optimization problems, and collaborate with global teams in research and development.

As a Senior Software Engineer on the Car Experience team, you will guide backend development and machine learning data pipelines focused on enhancing rider experience in autonomous vehicles.

Develop and optimize the ML training framework in high-performance C++, implement new ops and layers, debug and tune model performance on Tenstorrent chips, collaborate with compiler and kernel teams, and support integration and productionization of real-world models.

Design and implement document intelligence pipelines; develop ML models; optimize data processing systems; establish evaluation frameworks; collaborate with experts.

The role involves conducting R&D in machine learning, particularly in model training and architecture development. Candidates should have a background in deep learning and experience in hands-on experiments with foundational models.

Design, build, and operate large-scale geospatial data pipelines and production ML/agent systems. Own data ingestion, distributed processing, model training, deployment, monitoring, and observability. Develop backend services and tooling, integrate agent frameworks, collaborate with product and customer teams to drive revenue and reliability.

The Machine Learning Engineer II will develop and optimize ML models, process large datasets, and integrate ML solutions while collaborating with peers and staying up to date on technologies.

As a Senior Machine Learning Engineer, you will design and deploy AI models, work on data pipelines, and enhance AI-driven retail solutions through collaboration with various teams.

Responsible for full-cycle recruiting for senior AI roles with a focus on sourcing talent in LATAM and Europe, managing pipelines, and closing candidates.

As a Senior Machine Learning Engineer, you will drive document parsing, improve algorithms, and mentor team members in computer vision tasks.

Design, implement, and deploy ML and AI solutions; architect AI systems; build and oversee data pipelines; collaborate with engineering teams; translate business needs to data problems; present results to stakeholders; follow Agile practices.

Lead the design and development of low-latency machine learning inference services, ensuring high availability and scalability, while collaborating with data scientists and cross-functional teams.

Develop and scale neural networks for source code tasks, create and improve methods for code generation, editing, and agent-based workflows, mentor colleagues, and produce publishable ML research results.

You will optimize ML infrastructure, automate ML pipelines, manage versioning, and collaborate with engineers to ensure model scalability and reliability.

Conduct applied AI/ML research to solve home design challenges, work with raw data, test hypotheses, and build prototypes/MVP solutions.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.