Senior ML Operations Engineer

• Join our team as a Sr MLOps Engineer to help us bring current and next generations of Pod ML models to life
• You’ll be a part of a small team designing and implementing solutions with high levels of autonomy to bring our members better sleep
• Your work will go directly to our fleet of existing Pods with low friction and direct impact to the business
• We are a fast moving and fast growing company, and we embrace individuals with a growth mindset and strong desire to help us achieve our mission: Improving people’s lives through optimal sleep
• Pioneer Cutting-Edge Technology: Introduce and implement cutting-edge ML technologies, integrating them into our products and processes to enable the future of health monitoring
• End-to-End Ownership: Own design and operation of robust ML infrastructure – building scalable data, model, and deployment pipelines that ensure reliable delivery of models to production
• Cross-functional Collaboration Partner with R&D, firmware, data, and backend teams to ensure ML inference operates reliably and scales to Pods everywhere
• Optimize for Performance: Drive cost-effective, scalable, and high-performance ML systems by optimizing compute, storage, and deployment resources across training and inference
• Enhance Tooling and Platforms: Develop tooling, micro services, and frameworks to streamline data processing, experimentation, and deployment
• Effective Remote Communication: Thrive in a remote work environment, ensuring clear and direct communication
• From your first day, you’ll take on substantial responsibilities that have a direct impact on our core business and product success
• We are a small team that empowers you to own your projects and see the tangible effects of your efforts, enhancing both your professional growth and our company’s trajectory
• Your path will be challenging but rewarding, perfect for those who thrive in fast-paced environments aiming for high standards

Benefits

• Flexible PTO
• Paid parental leave
• Comprehensive medical insurance
• Your own Pod
• Pet-friendly offices
• Equity participation & periodic refreshes
• Fast career growth & salary progression
• Weekly fitness classes in our offices
• Work directly with founders and executives
• 5 in-person offices in NYC, Boston, SF, Shenzhen and Milan- Proven Expertise: 5+ years of software engineering experience with a focus on ML infrastructure, distributed systems, or large-scale data processing in Python (e.g., PyTorch, TensorFlow, or similar)
• Adaptive Problem Solver: A fast-paced, collaborative, and iterative approach to tackling complex problems
• Cloud-Native Expertise: Strong experience with AWS (Lambda, ECS, DynamoDB, CloudWatch) or equivalent cloud platforms for serving and monitoring ML systems
• Scalable Deployment Experience: Demonstrated success shipping ML models to production at scale, handling telemetry, monitoring, and feedback loops across large device fleets or user populations
• ML Operations Mastery: Hands-on experience with ML workflow orchestration and CI/CD pipelines for model deployment
• Familiarity with health, wellness, or IoT domains, especially wearables or medical-grade devices
• Understanding of secure ML operations, privacy practices, and compliance considerations, particularly for health-related or IoT data
• Demonstrated expertise in optimizing ML infrastructure for efficiency, latency, and cloud cost at scale
• Expertise in real-time ML workflows and streaming systems (e.g., Kinesis, Kafka, Flink)