MLOps Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and manage the ML lifecycle platform. Take ownership of the tools that ensure model development is both reproducible and production-ready, featuring MLflow (or equivalent systems) at its core: experiment tracking, model registry, artifact and metadata management, and versioned, repeatable training and inference pipelines.

• Oversee CI/CD and deployment for ML workloads. Construct automated pipelines that transition models from notebooks to production securely, encompassing packaging, containerization, automated testing and validation, staged rollouts, and rollback strategies.

• Ensure models are observable and reliable in production. Implement monitoring for model and service health, including latency, drift, data quality, and cost signals, equipped with alerting mechanisms and clear runbooks to facilitate quick issue resolution.

• Establish the cloud-native foundation. Contribute to and manage containerized workloads on Kubernetes and formalize infrastructure using infrastructure-as-code tools such as Terraform, ensuring environments remain consistent, secure, and reproducible.

• Set up meaningful guardrails. Apply infrastructure-level governance for ML systems, including access controls, deployment policies, and auditability, collaborating with security and compliance teams to meet our risk and regulatory standards.

• Empower and guide the teams you assist. Create repeatable patterns and shared services that alleviate friction for data and application teams, offer technical mentorship to junior engineers, and help shape the direction of dv01's MLOps practices.

⛳️ Requirements

• 4–7 years of pertinent experience in platform engineering, DevOps, or MLOps, with robust experience managing systems in production environments.

• Practical experience with ML lifecycle tooling. You have built or operated experiment tracking, model registry, and pipeline workflows using MLflow or similar platforms (e.g., Weights & Biases, Kubeflow, SageMaker, Vertex AI Pipelines). This experience is vital for the role.

• Strong expertise in cloud-native infrastructure. You are comfortable working with Kubernetes, containerized workloads, and infrastructure-as-code tools such as Terraform.

• Proficiency in CI/CD processes. You have designed and sustained automated build, test, and deployment pipelines, ideally for ML or data-focused workloads.

• Solid skills in Python/Go and familiarity with supporting PyTorch-based production systems (deploying, serving, and operating them, not necessarily authoring the models).

• An operational and security-focused mindset. You possess an understanding of infrastructure security, IAM, secrets management, and operational risk, and you design with secure, reliable defaults.

• Strong communication and collaboration abilities. You work effectively across functions, can mentor and provide technical guidance, and are adept at making pragmatic decisions in ambiguous problem spaces.

🏝️ Benefits

• Unlimited PTO. Take the time you need to recharge, whether that means enjoying a beach vacation or taking a mental health day at home.

• $1,000 Learning & Development Fund. Regardless of your career stage, we encourage continual investment in your future through conferences, classes, and workshops. We also organize hackathons, brunch & learns, and other employee-led learning activities.

• Remote-First Environment. We believe people flourish in a flexible and supportive setting. Work from your home, a cafe, or a hotel—it's your choice.

• Health Care and Financial Planning. We provide a comprehensive medical, dental, and vision insurance package for you and your family, along with a 401(k) plan for your contributions.

• Stay active your way! Receive $138/month toward your preferred gym or fitness membership, or utilize up to $1,650 annually through our Fitness Fund for workout equipment, gear, or other wellness essentials.

• New Family Bonding. Primary caregivers are entitled to 16 weeks of fully paid leave, while secondary caregivers can take 4 weeks. We understand that returning to work after welcoming a new child can be challenging, which is why we are flexible and empathetic to the needs of new parents.