Senior Machine Learning Operations Engineer II – AI Native

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $148k - $216k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

info
Apply Now
Find Similar Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Logo of Life360

Life360

201 - 500 employees

Founded 2008

👥 B2C

📡 Telecommunications

💰 Post-IPO Equity on 2022-11

B2C • Safety • Telecommunications

Life360 is a leading family safety app that offers a comprehensive suite of services for location and digital safety. With Life360, users can effortlessly share their location, track their phones, and manage driving safety measures, including crash detection and 24/7 roadside assistance. The app includes features for digital safety, such as identity theft protection and SOS alerts, ensuring protection and prevention for each family member. Life360's plans, which include free, Gold, and Platinum options, are designed to accommodate various needs, offering peace of mind with advanced safety and coordination tools. The app is trusted by millions of users and is highly rated on app stores for its efficiency and reliability in connecting family members and ensuring their safety.

📋 Description

• 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. • Observability & Monitoring: Establish unified logging, alerting, and monitoring solutions to track model inference performance, system latency, resource utilization, data drift, and concept drift. • 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. • Data 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 practices.

🎯 Requirements

• 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. • Programming Mastery: Strong proficiency in Python, including deep familiarity with software engineering best practices (unit testing, modular design, version control via Git). • Orchestration & Containerization: In addition to hands-on experience with containerization (Docker) and container orchestration platforms, specifically Kubernetes (EKS, GKE, or native clusters), experience with related tools like FastAPI. • 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. • Cloud Foundations: Practical experience operating within a major cloud ecosystem—e.g., AWS, GCP, Databricks—with a clear grasp of cloud networking, security, and storage tiers. • Strong communication and project leadership skills, with the ability to influence cross-functional teams. • Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, or a closely related quantitative field.

🏖️ 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. • 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.

Apply Now

Similar Jobs

🔥 12 hours ago

NBCUniversal

10,000+ employees

📱 Media

Deep Learning Engineer implementing core algorithms for media datasets at NBCUniversal. Collaborating with cross-functional teams to turn high dimensional data into high-fidelity content.

🔥 13 hours ago

Paramount

10,000+ employees

📱 Media

👥 B2C

Lead Machine Learning Operations Engineer at Paramount overseeing reliability and governance of ML systems. Focus on production health, incident response, and operational rigor.

🔥 17 hours ago

AvaSure

201 - 500

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Manager of AI/ML leading a team of machine learning engineers at AvaSure. Responsible for the architecture and execution of the ML lifecycle and ensuring production AI systems are scalable and reliable.

🔥 18 hours ago

NVIDIA

10,000+ employees

🤖 Artificial Intelligence

🎮 Gaming

Senior Perception Engineer at NVIDIA developing end2end solutions for autonomous driving perception. Working on deep learning models and data-driven development for real-world driving scenarios.

🔥 19 hours ago

System Inc.

11 - 50

🤖 Artificial Intelligence

🔬 Science

Data & AI/ML Engineer at System designing data pipelines and infrastructure for healthcare data products. Ensuring reliability and performance while partnering with Research and Data Science teams.