Top Machine Learning Jobs in Krakow

Design and implement backend services and APIs in Go, collaborate with cross-functional teams, maintain platform stability and scalability, communicate proactively, and contribute to team planning and continuous improvement.

The Fund Accounting Director leads NAV processes, manages accounting teams, ensures timely delivery, and collaborates with clients and internal departments while resolving issues and enhancing procedures.

The role involves designing MLOps platforms, implementing CI/CD pipelines, monitoring model performance, and collaborating with data scientists to productionize ML models. Mentorship to juniors is encouraged.

The Commercial Analytics Manager will lead investigations into KPI shifts, mentor Brand Analysts, and oversee brand health. The role bridges business and data science, ensuring optimal business growth and data-driven decision-making.

Lead design and implementation of threat detection features for on-prem and hybrid identity environments. Build scalable backend services, integrate product capabilities across the ITDR portfolio, apply AI/ML for anomaly detection, and mentor engineers. Collaborate with product and platform teams to align architecture, security, and operational practices for enterprise deployments.

Lead and deliver statistical support for Phase II-III clinical trials embedded with a sponsor: design input, SAP/sample size, interim/final analyses, oversight of programmers/statisticians, regulatory submissions, and collaborate cross-functionally to ensure compliant, high-quality statistical deliverables. Apply advanced statistical methods and ML/DL for analytics and process automation.

Work with AAA developers to optimize GPU/system performance for path-traced and neural rendering, develop and tune neural rendering algorithms and AI models, profile and optimize low-level performance, collaborate with architecture and driver teams, and create demos, papers, and presentations for conferences.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Lead the deployment and management of ML/DL models, design systems for dataset management, and optimize model serving processes in production.

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.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

The Customer Value Architect will engage with customers to ensure the effective adoption and value realization of the Neara platform, focusing on ROI metrics and customer relationships.

The Customer Success Manager will onboard and support Portuguese utility accounts, ensuring effective use of digital twin technology and driving long-term partnerships and customer satisfaction.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

Manage the end-to-end product lifecycle for financial crime tools, focusing on compliance, innovation, and backlog management while liaising between engineering and business teams.

Lead design and delivery of ML solutions for perception, prediction, and planning for assisted and automated parking. Define CV and multimodal sensor-fusion approaches, drive architecture from data pipelines through deployment, establish evaluation metrics, mentor engineers, and collaborate with global teams to improve algorithms and production performance.

Design and optimize ML models for perception, prediction, and planning in automotive parking systems. Build computer-vision and multi-sensor processing solutions, trajectory forecasting, training/evaluation pipelines, analyze large datasets, validate models in real-world scenarios, and collaborate with software, systems, and product teams to improve algorithms and tools.

Lead statistical strategy and delivery for Phase I-IV clinical trials embedded with a pharmaceutical sponsor. Design analyses, support protocol and reporting activities, oversee programming/CRO work, apply SAS/R (R Shiny)/Python and ML/DL methods for analyses and automation, and mentor junior statisticians.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead the Weaviate Database product: own roadmap and strategy, translate customer and research insights into features across schema, storage, replication, and search quality, coordinate cross-functional teams, drive developer adoption, and measure feature outcomes post-release.

Design, implement, deploy, and monitor scalable ML pipelines and experiments. Develop production-quality code, CI/CD, containerized deployments, unit tests, and troubleshooting. Support customers and stakeholders with demos, documentation, and sales/operations support. Work with LLMs, AI agents, and advanced statistical/numerical methods.

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Lead product strategy and roadmap for query interpretation and search quality. Own models, tools, and metrics to optimize recall and precision. Collaborate with ML, infra, and product teams, triage quality issues, benchmark competitors, and build evaluation frameworks and explainability for search results.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.