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Top Machine Learning Jobs in Poland
The Business Lead will develop a strategic vision to leverage Customer Data to enhance user engagement and advertising monetization. Responsibilities include aligning data goals across business objectives, creating data governance policies, collaborating with cross-functional teams, and managing projects related to customer data initiatives.
The Solution Architect for Digital Transformation will design and implement technology solutions for banking transformation, collaborating with stakeholders to align architectures with strategic and regulatory goals. Responsibilities include high-level design reviews, architecture recommendations, and ensuring solutions meet industry standards while driving adoption of modern practices like DevOps and microservices.
As a Principal Software Engineer, you will lead the R&D efforts for HERE Navigation Assistant, focusing on algorithm development, system architecture, and data analysis. Responsibilities include creating efficient algorithms, mentoring team members, and preparing technical documentation while collaborating with cross-functional teams.
As a Supply Chain AI/ML Engineer, you will develop and deploy machine learning models to optimize supply chain operations, enhance forecasting accuracy, improve inventory management, and streamline logistics. Collaborating with data scientists and analysts, you'll design solutions, conduct data analysis, and integrate models into existing systems, focusing on accuracy and reliability while staying current with industry advancements.
The Head of Consumer Products at ABBYY is responsible for developing and executing strategies for high-quality support of consumer products. Key duties include refining KPIs, implementing improvements based on metrics, managing team performance, enhancing customer satisfaction, and collaborating with cross-functional teams to align support operations with business goals.
The Director of Machine Learning and AI at Visa will lead a team in executing the machine learning strategy, developing and deploying models, and driving innovation in products and services. The role requires technical leadership, collaboration with senior leadership, and representation of the company's capabilities in industry forums.
The Data Engineering Manager leads data engineering and data science teams, focusing on building scalable data solutions and maintaining AI/ML systems. Responsibilities include hiring talent, providing technical oversight, driving project architecture, and establishing best practices in engineering and data science.
As an ML Ops Engineer at Capco Poland, you will develop, deploy, and maintain ML infrastructure, automate processes, monitor ML models, optimize cloud resources (GCP), and collaborate with Data Science teams. You'll be responsible for ensuring the full ML lifecycle and utilizing CI/CD best practices.
As the Senior Manager of Records to Report (R2R), you will oversee the R2R team, managing compliance with accounting policies, closing activities, and financial reporting. You'll drive efficiency through standardization and automation, champion digital enablement using technologies like AI and RPA, and lead financial integration strategies while mentoring your team for continuous development.
As a Senior ML Engineer, you will lead the development of the company's computer vision capabilities, managing data labeling, building ML training pipelines, and ensuring models are deployed and maintained effectively to support key client features.
The Senior Machine Learning Engineer IV at OpenX will enhance and maintain machine learning pipelines, streamline processes, optimize models, and collaborate with cross-functional teams to deliver robust infrastructure for model training and deployment.
The Principal Data Scientist will lead machine learning and NLP projects, mentor junior team members, and develop AI-driven solutions to enhance R&D processes and efficiencies. Responsibilities include data collection, model development, and communicating insights to stakeholders while ensuring adherence to best practices in data science and software engineering.
The Engineering Manager will lead a cross-functional team of engineers and data scientists focused on improving translations using AI and ML. Responsibilities include managing the technical roadmap, mentoring team members, ensuring best practices in software development, and collaborating with product management to meet business goals.
The Product Manager will lead product discovery and roadmap creation for ML-based solutions, collaborate with business stakeholders, and support the implementation of AI to address business challenges. Responsibilities include managing product backlogs, defining success metrics, and facilitating communication across teams to align objectives.
As a Senior Product Manager, you will drive the strategy and execution of Document AI at Snowflake. Responsibilities include defining the product roadmap, collaborating with engineers and data scientists, conducting market research, and guiding product development from conception to launch, all while ensuring alignment with customer needs and the company's strategic goals.
As a Senior Technical Project Manager, you will lead and manage data science projects, ensuring alignment with organizational priorities and adherence to best practices. You will facilitate communication between data teams and stakeholders, drive cross-functional collaboration, and focus on the sustainable implementation of scalable solutions.
As a Senior ML/Backend Engineer, you will design, develop, and deploy ML-driven applications. Your responsibilities include building CI/CD pipelines, managing cloud platforms, and integrating large language models. You'll collaborate with cross-functional teams to ensure the reliability and scalability of software solutions, leveraging your expertise in backend development and machine learning frameworks.
The Senior Machine Learning Engineer will lead the design and development of machine learning models and data processing pipelines, focusing on NLP and LLM technologies. Responsibilities include performing comprehensive data analysis, producing reports, and optimizing workflows for intelligent systems.
As a Back-End Software Engineer, you will lead the development of AI solutions and integrate data processing pipelines while collaborating closely with teams to enhance chatbot functionality and optimize system architecture.
As a Presales AI/ML Engineer at Neptune, you will present product capabilities to AI research teams worldwide, lead technical discussions, conduct demos, guide integrations, and maintain relationships with technical stakeholders to enhance product adoption.
The Engineering Manager will lead a team focused on data collection and analysis related to Corporate Social Responsibility using AI models. Responsibilities include managing the team, ensuring delivery quality, advancing applications, and coordinating with product teams to align business needs.
As an Application Development Engineer at Arista Networks, you will collaborate with cross-functional teams to develop and implement machine learning models and software tools, collecting and processing large data sets to solve complex business problems while ensuring the deployment and proper functioning of these systems.
The Expert ML Engineer will develop advanced machine learning algorithms for in-cabin sensing in vehicles, oversee software quality in Python/C++, improve ML workflows, mentor junior engineers, and engage in innovative technology projects within a collaborative Agile team.
As an ML Engineer, you will develop machine learning algorithms for in-cabin sensing, train deep neural networks, and tackle algorithmic challenges like object detection and tracking. Your role involves writing efficient software in Python and C++, working in an Agile SW development team, and contributing to the improvement of vehicle cabin safety and comfort.
As an Expert ML Simulation Engineer, you will develop advanced simulations and software tools for synthetic data generation in automotive applications, working closely with machine learning engineers. Responsibilities include modeling 3D assets, minimizing the domain gap for ML training, and ensuring high-quality, efficient Python software development.
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