Senior Machine Learning Engineer

Summary

Join IDOVEN, a health tech startup using AI to prevent cardiac disease, as an ML Engineer. You will be crucial in developing and maintaining the core infrastructure and tools for our machine learning engineers. This involves building solutions for data access, GPU resource management, experiment tracking, and model deployment. Backed by top investors, you'll contribute to a game-changing product. The role offers a dynamic remote work setup, professional development opportunities, and a collaborative team environment. IDOVEN is a fast-growing, award-winning company committed to innovation and making a difference in healthcare.

Requirements

• 3-4 years of experience in a similar ML platform engineering role, ideally with experience deploying models to production
• A strong passion for building robust and scalable ML platforms
• A solid understanding of optimization techniques, multithreading, and distributed system concepts
• A firm foundation in computer science principles, including data structures, algorithms, and algorithm complexity analysis
• Experience building and maintaining software systems, preferably in a cloud environment (e.g., AWS, GCP, Azure)
• Experience managing GPU resources, including driver management, access control, resource allocation, and memory management (NVidia, CUDA)
• Familiarity with machine learning frameworks such as TensorFlow or PyTorch
• Experience with experiment tracking and model management tools (e.g., MLflow, TensorBoard)
• Experience with containerization technologies (Docker, Kubernetes) and version control systems (e.g., GitHub)
• Excellent problem-solving, communication, and collaboration skills
• Ability to work both independently and as part of a team
• Comfortable with a CI/CD approach, code reviews and collaborative development practices

Responsibilities

• Design, develop, and maintain the tools and infrastructure that support our ML model training, experimentation, and deployment workflows
• Develop systems for efficient access to and management of large datasets
• Create solutions for optimizing GPU utilization and resource allocation
• Integrate and maintain experiment tracking and monitoring tools (e.g., MLflow, TensorBoard)
• Develop and implement the processes for deploying ML models to production environments
• Collaborate closely with ML engineers to understand their needs and provide effective solutions
• Contribute to improving our ML development lifecycle and best practices
• Troubleshoot and resolve issues related to the ML platform
• Stay current with the latest advancements in ML platform technologies and best practices

Preferred Qualifications

Experience with experiment tracking and model management tools (e.g., MLflow, TensorBoard)

Benefits

• Dynamic remote work setup that allows you to connect with our Madrid office, giving you the freedom to work from home 70% of your week or more!
• Learning and development opportunities and training budget
• Flexible Remuneration
• Health Insurance
• Access to Wellhub (Gympass), empowering your physical and mental wellness!
• 23 holidays, your birthday off, and December 24th and 31st half days to celebrate!
• Regular team events and Thursday happy hours