Top Machine Learning Jobs in Poland

Lead AI-driven consulting engagements, develop AI strategies, manage multidisciplinary teams, mentor junior colleagues, publish thought leadership, and build external network.

The EMEA Sales Leader will drive the company's expansion in the region, establish sales pipelines, develop partnerships, and oversee the sales team.

The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.

Responsible for delivering AI and data science solutions, driving AI fluency, and collaborating across teams to enhance analytics capabilities and business strategies.

Design and develop scalable, high-quality backend systems for traffic automated road closure detection, handling the full software development lifecycle.

The Customer Success Engineer will act as a technical expert and advisor, ensuring customers adopt Deepgram's voice technologies effectively, manage customer relationships, conduct demos, and drive growth opportunities.

Join Welo Data as part of a global community focusing on data annotation and enhancing AI models with diverse linguistic expertise.

The Data Scientist will design AI models using machine learning, train algorithms, deploy models to the cloud, and collaborate with teams to ensure data science solutions are effective and scalable.

Build and maintain ML model deployment platforms, ensuring reliability and scalability. Collaborate with AI engineers to optimize performance and handle alert issues.

Lead design and development of products from vehicle telematics data, collaborating across teams to enhance customer experience and maintain core platforms.

The Senior Director Analyst will conduct research and analysis in data management, focusing on trends, best practices, and emerging technologies, while supporting sales and client engagement.

As an R&D Engineer, you'll develop and validate AI/ML technologies for HVDC solutions, collaborate globally, and innovate optimization methods.

Lead the AI product strategy at Goodnotes, overseeing development across various AI initiatives and ensuring alignment with company vision.

Lead and implement a multi-year SCM continuous improvement strategy, utilizing Lean principles and advanced analytics to optimize processes, mentor teams, and deliver business results.

The Staff Machine Learning Scientist will lead product vision through innovation, overseeing the R&D lifecycle, mentoring junior team members, maintaining research standards, and advancing AI technology in conversational systems.

Develop and implement machine learning models for lead scoring, customer segmentation, and optimization, while collaborating across teams to drive data-driven strategies.

Design and improve end-to-end ML/AI pipelines, process datasets, and contribute production code for high-quality solutions in machine learning projects.

The Principal ML & AI Scientist will lead the development of AI and machine learning models to address business challenges, focusing on innovations in financial payments, while collaborating with cross-functional teams and automating predictive pipelines.

The Staff ML Scientist will drive AI research in payments data, focusing on machine learning innovations and collaborations to enhance Visa's products.

The Senior Product Manager - Capture leads AI-based invoice capture and validation, driving strategy and collaboration across teams to optimize document processing for accounts payable automation.

Promote Lean culture by improving processes and manufacturing excellence, training teams, and driving continuous improvement initiatives while collaborating across departments.

This role involves developing pricing strategies, forecasting models, analyzing profitability, and enhancing pricing processes using data analytics across the organization.

The role involves conducting R&D in process mining, proposing projects, collaborating with teams, implementing solutions, and disseminating results in publications.

The R&D Scientist will enhance simulation-based engineering processes using ML, lead research projects, collaborate globally, and publish findings.

Lead the design and implementation of scalable cloud-based data pipelines and architectures, ensuring best practices, compliance, and data quality.