Sr Software Engineer, MLOps

About the role

We are seeking a Sr MLOps Engineer to build the model lifecycle, deployment, observability, and infrastructure foundations used by multiple production AI features, including recognition, AI Video Search, Multimodal AI, Agentic AI, and Energy AI ship faster with shared, reliable platform primitives. In this role, you will be responsible for:

Responsibilities

• Build model registry, model serving, deployment, rollback, and CI/CD systems for production AI services.
• Own feature, dataset, model, and prompt versioning patterns across AI products.
• Standardize training, evaluation, release, monitoring, and operational workflows for AI teams.
• Improve reliability, cost efficiency, latency, and repeatability of AI launches.
• Create reusable platform patterns across AI features
• Partner with engineering, data science, product, and operations teams to productionize AI capabilities at scale.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 5+ years of professional experience in software development, applied science, or ML engineering; or
• Master’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 2+ years of professional experience in software development, applied science, or ML engineering
• Experience building production ML platforms, model serving systems, or MLOps workflows
• Strong Python and cloud engineering skills
• Experience with CI/CD, Git, infrastructure-as-code, and production monitoring
• Familiarity with model registry, feature/data versioning (DVC), validation, deployment, rollback, and observability
• Ability to communicate tradeoffs clearly across engineering, data science, and product teams

Preferred Qualifications

• Experience with GCP/AWS, Cloud Run, Kubernetes, Vertex AI, SageMaker, MLflow, or equivalent tools
• Experience with AI services for computer vision, LLMs, multimodal models, or recommendation systems
• Experience with data validation, dataset versioning, feature stores, or model quality monitoring
• Experience optimizing cost, latency, reliability, and operational readiness for AI systems
• Experience with IoT, edge AI, smart home, or distributed device environments

Benefits

• Paid holidays and flexible paid time away
• Employee/Friends/Family Discounts
• Medical/dental/vision/life coverage & 24/7 Medical Hotline
• 401(k) + Employer Match
• Employee Resource Groups

Pay

The base salary range for this position is: $150K to $180K*

*The base salary range above represents the low and high end of the salary range for this position. Actual salaries will vary based on several factors including but not limited to location, experience, and performance. The range listed is just one component of the total compensation package for employees. Other rewards may include annual bonus, short- and long-term incentives, and program-specific awards. In addition the position may be eligible to participate in the benefits program which include, but are not limited to, medical, vision, dental, 401K, and flexible spending accounts.

Schedule

The position will start remote and then will move into the hybrid schedule. Position requires in-office presence in Seattle, WA on a hybrid schedule for Monday, Tuesday, Wednesday, and Thursday with a work from home day on Friday.