AI Research Engineer, Phaidra

• You are passionate about bringing AI into the physical world and thrive at the intersection of theory and practical application
• 1+ years of prior experience in applied machine learning or software engineering
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field
• Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or JAX
• Strong foundations in supervised learning, reinforcement learning, or control systems
• Familiarity with common tools for experimentation (e.g., Ray, MLFlow, WandB, or similar)
• Ability to write high-quality, testable, and maintainable code
• Share our company values: Collaboration, Transparency, Operational Excellence, Ownership, and Empathy

Desirable

• Phaidra is looking for a creative and pragmatic Machine Learning Engineer to join our research team
• You will work closely with researchers, engineers, and customers to build, scale, and deploy intelligent systems in industrial environments
• You will have the opportunity to make immediate impact by helping design and implement learning-based control systems—pushing the boundaries of how AI interacts with complex, dynamic processes
• The ideal candidate enjoys owning end-to-end workflows—from prototyping to production—and is comfortable navigating both model development and software engineering
• Building robust ML pipelines for training, evaluation, and deployment of control algorithms
• Working with researchers to implement cutting-edge methods in Deep Learning and Reinforcement Learning
• Collaborating with software engineers to integrate models into real-time systems
• Designing tools and infrastructure to support large-scale experimentation and iteration
• Performing rigorous evaluations on simulation and real-world data, and tuning models for safety, performance, and robustness
• Supporting reproducibility and code quality across the team
• In your first 30 days..
• You’ll complete onboarding and gain context on Phaidra’s product, infrastructure, and research directions
• You’ll begin contributing to our ML libraries, experiment tooling, and data pipelines
• You’ll review past experiments, training setups, and our codebase
• By your first 60 days..
• You’ll take ownership of an ML pipeline or training experiment
• You’ll work with researchers to implement and validate new learning algorithms
• You’ll contribute to internal tooling that improves research velocity
• By your first 90 days..
• You’ll have a model or pipeline running in production or simulation
• You’ll have pushed significant improvements to our ML infra or core libraries
• You’ll be fully embedded in the team, contributing ideas and helping shape the next phase of research

• All of our interviews are held via Google Meet, and an active camera connection is required
• Meeting with People Operations team member (30 minutes)
• Initial Meeting with Hiring Manager (30 minutes)
• Technical Interview 1 (60 minutes)
• Technical Interview 2 (60 minutes)
• Culture fit interview with Phaidra’s co-founders (30 minutes)