Senior Machine Learning Engineer I

Responsibilities

• Own end-to-end systems and infrastructure for deploying multimodal and video models to reliable, scalable production.
• Design and operate large-scale video and multimodal data ingest, storage, processing, labeling, and retrieval pipelines.
• Build scalable training, evaluation, inference, and serving infrastructure for real-time and batch workloads.
• Develop retrieval, indexing, embedding, vector search, orchestration, and tool-use infrastructure for agentic reasoning.
• Ensure platforms are secure, privacy-preserving, and responsible by design.
• Set technical direction, raise engineering standards, and mentor other engineers.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or an equivalent highly technical field.
• 7+ years of software engineering experience and a track record architecting, operating, and maintaining large-scale distributed production platforms.
• Deep experience across the ML lifecycle, including data pipelines, training and evaluation infrastructure, model serving and inference, and production monitoring.
• Experience with high-volume video or multimodal data systems.
• Strong software engineering fundamentals and proficiency in Python, with familiarity with PyTorch or TensorFlow.
• Hands-on experience operating cloud infrastructure at scale with AWS, GCP, or Azure, including distributed systems and container orchestration.
• Ability to work across architecture, design, performance metrics, code, testing, project planning, deployments, and operations.
• Strong communication skills and experience partnering with scientists, engineers, and product managers.
• Master’s or PhD in a relevant technical field, video processing or understanding experience, retrieval or vector search experience, foundation model serving, agentic systems, LLM tool-use orchestration, and responsible AI or privacy-preserving experience are preferred.

Benefits

• Competitive salary and 401k with employer match.
• Discretionary paid time off and paid parental leave for all.
• Medical, dental, and vision plans.
• Fitness programs and emotional and mental wellness support.
• Learning and development programs and employee resource groups.
• Office snacks.
• Seattle-based hybrid schedule with onsite work Tuesday through Friday and remote flexibility on Mondays.