Life360

Life360

Senior Machine Learning Operations Engineer II (AI Native)

Remote, USA ; Remote, Canada · Senior

Sponsorship not specified$148k-$216kDetected 46 days ago
PythonGitSQLDatabricksAWSGCPDockerKubernetesTerraformCI/CDDevOpsAPI DevelopmentKafkaMachine LearningSparkdbtData EngineeringData ScienceLLMsAgentic AIMLOpsA/B TestingLeadershipCommunication

About the role

  • Data Science and Machine Learning (DSML) at Life360 is a lean, high-impact, matrixed team with individuals embedded in business units and working cross-functionally with Product, Analytics, Engineering, and business stakeholders.
  • We are dedicated to enhancing and optimizing the user experience, accelerating growth, and generating revenue through subscriptions, partnerships, and ads.
  • We are seeking a highly motivated and skilled Senior II MLOps Engineer.

Responsibilities

  • Infrastructure Management: Provision and optimize cloud-based ML infrastructure (including GPU/CPU computing clusters) utilizing Infrastructure as Code (IaC) paradigms.
  • Cross-Functional Collaboration: Work intimately with product development teams to drive infrastructure adoption and efficiency gains through SDK/API development, automation and efficient ML system maintenance.
  • Governance & Compliance: Implement robust lineage tracking for data, code, and model artifacts to ensure compliance, reproducibility, and security across the entire ML lifecycle.
  • Professional Experience: 5+ years of professional software engineering, DevOps, or data engineering experience, with at least 2 years dedicated to building and maintaining MLOps infrastructure.
  • Work intimately with product development teams to drive infrastructure adoption and efficiency gains through SDK/API development, automation and efficient ML system maintenance.
  • Implement robust lineage tracking for data, code, and model artifacts to ensure compliance, reproducibility, and security across the entire ML lifecycle.
  • Our company's mission driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference
  • Members Before Metrics - We focus on building an exceptional experience for families.

Requirements

  • Programming Mastery: Strong proficiency in Python, including deep familiarity with software engineering best practices (unit testing, modular design, version control via Git).
  • MLOps and Datastore Tooling: Proven familiarity with specialized ML lifecycle and data processing tools and platforms such as MLflow, Kubeflow, SparkML, Synapse ML, SQL, Spark/PySpark, dbt, and Airflow.
  • Strong communication and project leadership skills, with the ability to influence cross-functional teams.

Nice to have

  • Advanced Tooling: Experience implementing and scaling production feature stores (e.g., Feast, Tecton) and model registries.
  • Generative AI & LLMs: Prior experience deploying and optimizing Large Language Models (LLMs) or foundation models utilizing serving frameworks like vLLM, Triton Inference Server, or TGI.
  • Data Frameworks: Familiarity with distributed data computation engines such as Apache Spark, Ray, or Dask.
  • Experience in subscription-based products, lifecycle marketing, or user acquisition.
  • Experience in the consumer technology sector, particularly within a fast-paced and sometimes ambitious development setting.
  • Core Expectations
  • Problem-solving mindset - You structure ambiguous problems precisely before reaching for a tool, AI or otherwise
  • Collaborative approach - You can explain technical tradeoffs and articulate ideas effectively, work well across teams, and value diverse perspectives

Compensation

  • For candidates based in the US, the salary range for this position is $148,000 to $216,000 USD.

Benefits

  • Competitive 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.
  • Employee Assistance Program (EAP) for mental wellness.
  • Flexible PTO and 12 company wide days off throughout the year.
  • Learning & Development programs.
  • Pipeline Automation: Design, implement, and manage automated CI/CD and Continuous Training (CT) pipelines for machine learning model development, evaluation, and delivery.
  • Model Deployment: Containerize, deploy, and scale machine learning models as high-availability microservices or batch processing workflows.
  • 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 practices.
  • Equipment, tools, and reimbursement support for a productive remote environment.

Company info

  • We leverage a variety of technical skills and tools including experimentation, offline and online ML, online learning, and agentic AI (AI-Native development) to deliver exceptional customer value.
  • About the Job
  • In this role, you will bridge the critical gap between machine learning model development and core system operations.
  • You will be responsible for designing, building, and scaling the infrastructure and automated pipelines required to reliably train, deploy, and monitor our machine learning models in production environments.
  • You will join a fast-paced, collaborative team of data scientists, data engineers, and software architects.
  • In this position you will be empowered to mature our CI/CD systems, optimize distributed infrastructure, and directly impact the reliability and scale of our core AI-driven products.
  • This role requires strong technical expertise and practical experience in deploying machine learning inferences and models as well as the ability to collaborate with cross-functional teams to drive measurable business outcomes.
  • For candidates based in the US, the salary range for this position is $148,000 to $216,000 USD.
  • For candidates based out of Canada, the salary range for this position is $171,500 to 201,000 CAD.
  • We take into consideration an individual's background and experience in determining final salary - therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience.
  • The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.
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This listing is sourced directly from Life360's careers page and normalized into a canonical job model.