[Remote] Senior Machine Learning Operations Engineer II (AI Native)

Note: The job is a remote job and is open to candidates in USA. Life360 is a company dedicated to keeping families connected and safe through innovative mobile applications and tracking devices. They are seeking a Senior Machine Learning Operations Engineer II to design and manage the infrastructure and automated pipelines for machine learning models, ensuring their reliable deployment and monitoring in production environments.ResponsibilitiesPipeline Automation: Design, implement, and manage automated CI/CD and Continuous Training (CT) pipelines for machine learning model development, evaluation, and deliveryModel Deployment: Containerize, deploy, and scale machine learning models as high-availability microservices or batch processing workflowsObservability & Monitoring: Establish unified logging, alerting, and monitoring solutions to track model inference performance, system latency, resource utilization, data drift, and concept driftInfrastructure Management: Provision and optimize cloud-based ML infrastructure (including GPU/CPU computing clusters) utilizing Infrastructure as Code (IaC) paradigmsCross-Functional Collaboration: Work intimately with product development teams to drive infrastructure adoption and efficiency gains through SDK/API development, automation and efficient ML system maintenanceGovernance & Compliance: Implement robust lineage tracking for data, code, and model artifacts to ensure compliance, reproducibility, and security across the entire ML lifecycleData Infrastructure & Tooling: Work with data engineering to improve the data ecosystem, ensuring robust, scalable pipelines for experimentation and ML (including streaming tools like Kafka and Flink for low-latency online inference)Thought Leadership: Act as a mentor and thought leader, helping to define best practices in machine learning engineering, scalable ML service ops, and agentic AI (AI-Native) best practicesSkills5+ years of professional software engineering, DevOps, or data engineering experience, with at least 2 years dedicated to building and maintaining MLOps infrastructureStrong proficiency in Python, including deep familiarity with software engineering best practices (unit testing, modular design, version control via Git)Hands-on experience with containerization (Docker) and container orchestration platforms, specifically Kubernetes (EKS, GKE, or native clusters), experience with related tools like FastAPIProven familiarity with specialized ML lifecycle and data processing tools and platforms such as MLflow, Kubeflow, SparkML, Synapse ML, SQL, Spark/PySpark, dbt, and AirflowPractical experience operating within a major cloud ecosystem—e.g., AWS, GCP, Databricks—with a clear grasp of cloud networking, security, and storage tiersStrong communication and project leadership skills, with the ability to influence cross-functional teamsBachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or a closely related quantitative fieldExperience implementing and scaling production feature stores (e.g., Feast, Tecton) and model registriesPrior experience deploying and optimizing Large Language Models (LLMs) or foundation models utilizing serving frameworks like vLLM, Triton Inference Server, or TGIProficient with IaC frameworks, particularly Terraform, to manage reproducible environmentsFamiliarity with distributed data computation engines such as Apache Spark, Ray, or DaskRelevant cloud or architecture credentials, such as AWS Certified Machine Learning Specialty, Google Cloud Professional Machine Learning Engineer, or Certified Kubernetes Administrator (CKA)Experience in subscription-based products, lifecycle marketing, or user acquisitionExperience with geospatial data and mobile location-based servicesExperience in the consumer technology sector, particularly within a fast-paced and sometimes ambitious development settingBenefitsCompetitive pay and benefits.Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.Employee Assistance Program (EAP) for mental wellness.Flexible PTO and 12 company wide days off throughout the year.Learning & Development programs.Equipment, tools, and reimbursement support for a productive remote environment.Free Life360 Platinum Membership for your preferred circle.Company OverviewLife360 creates a mobile app for families that helps families feel closer together. It was founded in 2008, and is headquartered in San Francisco, California, USA, with a workforce of 501-1000 employees. Its website is http://www.life360.com.