Machine Learning Engineer

Reqroute, Inc; United States; Remote; USD 100,000 - 720,000; Full time

Job summary

A premier technology firm is seeking an AI ML Ops Lead to enhance production systems for machine learning. The role involves designing CI/CD pipelines, automating workflows, and ensuring the scalability of ML systems. Ideal candidates possess significant experience, strong Python skills, and familiarity with various ML frameworks and cloud platforms.

Qualifications

• 8-10+ years of experience in DevOps, ML Ops, or ML Engineering.
• Proficiency in Python and ML frameworks like TensorFlow and PyTorch.
• Experience with Docker and Kubernetes.

Responsibilities

• Design and implement CI/CD pipelines for ML models.
• Automate model training, testing, deployment, and monitoring workflows.
• Monitor model performance and data drift in production.

Skills

Python

ML frameworks

Containerization

Orchestration

Cloud platforms

CI/CD tools

Monitoring tools

Education

Bachelor’s or Master’s in Computer Science

Job description

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Job Title: AI ML OPS lead

Location: Remote (EST time zone only )

Term: Contract

Job Summary:

We’re looking for a skilled AI/ML Ops Engineer to bridge the gap between machine learning development and scalable, reliable production systems. You’ll be responsible for building and maintaining the infrastructure that enables rapid experimentation, deployment, and monitoring of ML models in real-world environments.

Key Responsibilities:

Design and implement CI/CD pipelines for ML models.

Automate model training, testing, deployment, and monitoring workflows.

Collaborate with data scientists to productionize ML models.

Manage model versioning, reproducibility, and rollback strategies.

Ensure scalability, security, and compliance of ML systems.

Monitor model performance and data drift in production.

Optimize infrastructure for cost and performance.

Required Qualifications:

8-10+ years of experience in DevOps, ML Ops, or ML Engineering.

Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch).

Experience with containerization (Docker) and orchestration (Kubernetes).

Familiarity with cloud platforms (AWS, Azure, or GCP).

Strong understanding of CI/CD tools (e.g., GitHub Actions, Jenkins).

Knowledge of monitoring tools (e.g., Prometheus, Grafana).

Preferred Qualifications:

Experience with feature stores and model registries (e.g., ML flow, Feast).

Understanding of data governance and responsible AI practices.

Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  Information Services

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