ML Platform Engineer: Build Scalable MLOps & Deployments

Jobtailor; Burbank (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor in California is seeking a senior ML/Data Science engineer to design and implement a greenfield ML platform. You will work closely with Data Scientists to understand their needs and with stakeholders to align deployments with business goals.

The role emphasizes integrating cutting-edge ML/MLOps practices, containerized development, and reliable deployment workflows. A background check is required and the team values pragmatic, scalable solutions.

Qualifications

• 3+ years experience in Data Science and ML Engineering.
• Strong Python development experience in a team setting.
• Design and implement MLOps platforms in a cloud environment.
• Experience building CI/CD workflows for model deployments.
• Experience developing containerized applications.
• Ability to innovate without over-engineering.
• Familiarity with common statistical and ML models and methods.
• Strong focus on deployment reliability.
• Background check clearance required.

Responsibilities

• Design and implement a greenfield ML platform to scale the Data Science team’s impact.
• Collaborate with Data Scientists to understand development needs.
• Collaborate with stakeholders to align model deployments with business problems.
• Evaluate and integrate cutting-edge software and practices in Data Science and MLOps.
• Refactor scripts/workflows into modular skills.

Skills

Python

ML Engineering

MLOps

CI/CD

Containerization

ML models

Reliability

Tools

Docker

Kubernetes

Job description

Jobtailor in California is seeking a senior ML/Data Science engineer to design and implement a greenfield ML platform. You will work closely with Data Scientists to understand their needs and with stakeholders to align deployments with business goals.

The role emphasizes integrating cutting-edge ML/MLOps practices, containerized development, and reliable deployment workflows. A background check is required and the team values pragmatic, scalable solutions.