Description

• Master’s or PhD in Computer Science, Machine Learning, Statistics, or a closely related field; or equivalent applied experience.
• Six or more years of combined research and applied ML engineering experience.
• Strong proficiency in Python and modern ML frameworks such as PyTorch or JAX.
• Hands-on experience training, fine-tuning, and evaluating deep learning models at non-trivial scale.
• Solid grounding in mathematics, statistics, and the theoretical foundations of modern ML.
• Experience taking ML models from research prototype to production with appropriate observability and safeguards.
• Familiarity with distributed training, mixed-precision training, and accelerator hardware.
• Strong written and verbal communication skills, including ability to explain complex methods clearly.
• Demonstrated ability to read, evaluate, and adapt techniques from current research literature.
• Track record of shipping impactful applied AI projects.

Preferred Qualifications

• Published research at top-tier AI/ML venues.
• Experience with large language model training, fine-tuning, or evaluation.
• Familiarity with retrieval-augmented generation, agentic systems, or multimodal architectures.
• Exposure to responsible AI, model evaluation, and alignment practices.
• Experience contributing to open-source ML projects

Key Skills

Education

Master's degree