Senior Machine Learning Operations Engineer II

About the role

Life360 is seeking a Senior Machine Learning Operations Engineer II to build and scale the infrastructure that powers our AI-driven products. You will ensure our machine learning models are reliably trained, deployed, and monitored in production, working closely with data scientists and engineers. This role is key to enhancing user experience and driving business growth through AI.

Key facts

What you'll do

• Develop and maintain automated pipelines for machine learning model training, evaluation, and deployment.
• Containerize and deploy machine learning models as scalable microservices or batch jobs.
• Implement comprehensive monitoring and alerting for model performance, system health, and data drift.
• Manage and optimize cloud-based machine learning infrastructure using Infrastructure as Code.
• Collaborate with product teams to integrate ML systems and improve efficiency.
• Establish lineage tracking for data, code, and model artifacts for compliance and reproducibility.
• Enhance data pipelines and tooling to support experimentation and low-latency inference.
• Mentor team members and define best practices for machine learning engineering and AI-Native development.

Requirements

• 5+ years of professional experience in software engineering, DevOps, or data engineering, with at least 2 years focused on MLOps infrastructure.
• Strong proficiency in Python and software engineering best practices, including Git.
• Hands-on experience with Docker and Kubernetes (EKS, GKE, or native clusters), and tools like FastAPI.
• Familiarity with MLOps and data processing tools such as MLflow, Kubeflow, SparkML, Synapse ML, SQL, Spark/PySpark, dbt, and Airflow.
• Experience with major cloud platforms like AWS or GCP, including cloud networking, security, and storage.
• Excellent communication and project leadership skills.
• Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or a related quantitative field.

Nice to have

• Experience with production feature stores (e.g., Feast, Tecton) and model registries.
• Experience deploying and optimizing Large Language Models (LLMs) or foundation models with serving frameworks like vLLM, Triton Inference Server, or TGI.
• Proficiency with Infrastructure as Code tools, particularly Terraform.
• Familiarity with distributed data computation engines like Apache Spark, Ray, or Dask.
• Relevant cloud or architecture certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Machine Learning Engineer, CKA).
• Experience with subscription products, lifecycle marketing, or user acquisition.
• Experience with geospatial data and mobile location-based services.
• Experience in the consumer technology sector.

Skills & tools

• Python
• Git
• Docker
• Kubernetes (EKS, GKE)
• FastAPI
• MLflow
• Kubeflow
• SparkML
• Synapse ML
• SQL
• Spark/PySpark
• dbt
• Airflow
• AWS
• GCP
• Terraform
• Apache Spark
• Ray
• Dask
• vLLM
• Triton Inference Server
• TGI
• Feast
• Tecton

Practical notes

• US Salary Range: $148,000 - $216,000 USD
• Canada Salary Range: $171,500 - $201,000 CAD
• Compensation includes base pay, equity, and a benefits package.
• Benefits include medical, dental, vision, financial, and other plans.
• 401(k) with company match (US) or RRSP with DPSP (Canada).
• Employee Assistance Program for mental wellness.
• Flexible Paid Time Off and 12 company holidays.
• Learning & Development programs.
• Support for remote work environment setup.
• Free Life360 Platinum Membership.
• Life360 is an AI-Native company; AI tool usage during interviews will be guided by the recruiter.
• All positions are remote-first within the US and Canada.