Senior ML Operations (MLOps) Engineer

Eight Sleep, Inc.; United States; Remote; USD 150,000 - 190,000; Full time

Job summary

Eight Sleep, Inc. seeks a Sr MLOps Engineer to bring current and next generations of Pod ML models to life. You’ll join a small team designing autonomous ML infrastructure that directly impacts our sleep technology and member experience.

The role emphasizes end-to-end ownership of data, models, and deployment pipelines, with a focus on scalable, high-performance ML systems across a rapidly growing platform.

Qualifications

• 5+ years of software engineering experience with a focus on ML infrastructure, distributed systems, or large-scale data processing.
• Proven expertise in Python and modern ML frameworks such as PyTorch or TensorFlow.

Responsibilities

• Design and operate robust ML infrastructure
• Build scalable data, model, and deployment pipelines
• Collaborate with RD, firmware, data, and backend teams
• Optimize compute, storage, and deployment for cost and performance
• Develop tooling and platforms to streamline data processing and experimentation
• Communicate effectively in a remote work environment

Skills

Python

ML infrastructure

Distributed systems

Data processing

Tools

PyTorch

TensorFlow

Job description

Join the Sleep Fitness MovementAt Eight Sleep, we're on a mission to fuel human potential through optimal sleep. As the world's first sleep fitness company, we're redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data-driven recovery experience.

Every role at Eight Sleep is a chance to create cutting-edge technology, collaborate with world-class talent, and help shape a future where sleep isn't passive, it's a powerful tool for living better. If you're tired of the ordinary and driven to build at the edge of what's possible, this is your moment.

High Standards. No Apologies.We operate with intensity because our mission demands it. At Eight Sleep, we bring the same mindset as the world's top performers: focused, relentless, and always pushing to be in the top 1% of our craft. This isn't a 9-to-5. Our team is deeply committed, often putting in the extra effort, not because we're told to, but because we're invested in building something category-defining.

The Role

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.

How you’ll contribute

• 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.

What you need to succeed

• 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).
• ML Operations Mastery: Hands-on experience with ML w