Top Machine Learning Jobs in Valencia

As a Senior Product Manager, you will define product vision, analyze market trends, manage product KPIs, and collaborate with teams to deliver innovative solutions.

Lead the development and implementation of a financial crime prevention product, shaping the product strategy and roadmap in a high-growth environment.

The Senior Product Manager will own and drive the development of Kraken's Algorithmic Execution & Strategy Engine, focusing on execution algorithms, API specifications, and client engagement to optimize trading strategies.

Lead the development of AI/ML systems for real-time applications, mentor teams, optimize performance, and contribute to the AI/ML community.

Design, build, and deploy ML-powered LiveOps tools: end-to-end ML projects from data transformation and modeling to deployment, monitoring, and iteration. Collaborate with engineers, product, and LiveOps/Game Design teams to empower gameplay experiences and troubleshoot the automation tool suite.

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

The Principal Product Manager will drive the strategy for AI-based pricing and reconciliation across travel services, manage model lifecycles, and ensure operational integrity in real-time financial data processing in collaboration with cross-functional teams.

Join Vizzuality's talent pool to contribute to sustainability efforts through science, data, design, and project management roles. Apply with your CV and cover letter to be considered when vacancies arise.

As a Machine Learning Engineer at Incode, you'll design and deploy deep learning models for identity verification technologies, collaborating on innovative solutions and optimizing ML pipelines for performance and cost efficiency.

As a Senior Engineer, you will develop a scalable ML Platform, enhance data pipelines, collaborate with teams, and mentor junior engineers while driving ML best practices.

Lead design, build, and deployment of ML solutions across the product lifecycle, including feature engineering, training, evaluation, and monitoring. Collaborate with product and engineering to deliver measurable impact, implement reliable pipelines, improve reproducibility and observability, and communicate model behavior to stakeholders while promoting code quality and responsible ML practices.

Lead the development of robot policies, focusing on task planning, computer vision, and decision-making in robotics. Mentor teams, drive technical roadmaps, and collaborate on scalable AI 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.

As a Lead Machine Learning Engineer, you will oversee complex projects, mentor teams, drive ML practices, and shape technical strategy.

Lead the development of robot policies and task planning. Collaborate with cross-functional teams to create real-world robotics solutions, incorporating AI technologies and MLOps practices.

Lead the development of high-fidelity simulations and validation workflows for robotic systems, focusing on sensor simulation and mechanical modeling to ensure reliable performance in real-world and virtual environments.

As a Staff Machine Learning Engineer, you will develop machine learning solutions for online gaming, shape the ML roadmap, mentor junior engineers, and drive technical direction.

As a Senior AI/ML Engineer, you'll design and develop AI solutions, build production-level ML models, and implement MLOps practices. You'll work with a multidisciplinary team on cutting-edge projects, focusing on AI-powered software and deep learning techniques.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

As a Lead Machine Learning Engineer, you will design ML infrastructure, mentor engineers, and ensure deployment reliability while collaborating across teams.