ML Engineer, Applied AI

About this role

Machine Learning Engineer at an AI research company building applied AI systems for scientific workflows. You'll adapt frontier models for customer-specific needs through post-training, evaluation, and production deployment, working across research and engineering teams.

What you'll do

• Post-train and adapt models using SFT, DPO, PPO, and GRPO techniques for customer-specific scientific requirements
• Design and build evaluation frameworks to measure model quality, reliability, and fit for customer use cases
• Debug model failures using traces, logs, customer context, and scientific feedback
• Run experiments to improve model performance and translate results back into product improvements
• Collaborate with AI researchers to move model capabilities into production-quality systems
• Integrate model behavior into end-to-end product workflows with software engineering teams

What they're looking for

• Machine learning model training and adaptation
• Python and modern ML frameworks (PyTorch, JAX, or TensorFlow)
• Evaluation metrics design and experimental methodology
• Large language models and multi-modal models
• RL post-training techniques (RLHF, GRPO, DPO)
• Model debugging and production ML systems
• Retrieval-augmented generation and agentic AI systems
• Cross-functional collaboration and technical communication

Benefits

• Comprehensive medical, dental, and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with generous company holidays
• Paid parental leave
• Educational assistance program
• Company-subsidized lunch and commuter benefits