Machine Learning Platform

Location: Columbus, OH
Salary: $65.00 USD Hourly - $70.00 USD Hourly
Description:
Job Title: Senior Lead Engineer : Machine Learning Platform (Open-Source Stack)

Type: 3+ Months Contract to Hire

Location: Columbus, Ohio 43219(3 days onsite, 2 days remote)

Only W2 Contract

Job Description

We're hiring a senior lead engineer to build and scale the open-source machine learning platform that supports production models across multiple lines of business. This role sits at the intersection of MLOps, infrastructure, and secure software delivery - with a strong focus on enabling data scientists to move faster without sacrificing compliance or stability.

You'll work closely with platform, cloud, cyber, risk, and architecture teams to design and implement robust ML delivery patterns using tools like MLflow, Metaflow, Airflow, Argo, Helm, Docker, and Kubernetes. Your work will power both batch and real-time model deployments, including support for ML, large language models and GenAI applications.

This role is ideal for engineers who are passionate about scaling ML the right way - with clear boundaries, secure defaults, and reusable patterns that others can build on.

Responsibilities

• Build and maintain secure, scalable infrastructure for ML model training, testing, and deployment using open-source tools.

1. Create reusable deployment templates that standardize the path to production across teams.

1. Translate prototype models into resilient, monitored, and observable production systems.

1. Implement guardrails and controls that ensure compliance with internal standards (e.g., SR 11-7, ISO 42001).

1. Partner with data scientists to simplify onboarding to platform capabilities.

1. Establish CI/CD pipelines with hooks for testing, scanning, and validation of model code and artifacts.

1. Serve as a technical lead for cross-functional delivery efforts involving model onboarding and platform integration.

Required Qualifications

• 6+ years of experience in software, data, or ML engineering roles.

1. Strong hands-on experience with tools like MLflow, Metaflow, Airflow, or similar orchestration frameworks.

1. Production experience with Kubernetes, Docker, and Helm.

1. Deep understanding of Python and software engineering best practices.

1. Experience implementing CI/CD pipelines and infrastructure-as-code in a cloud or hybrid environment.

Preferred Qualifications

• Experience working in regulated industries or environments with strong risk and compliance expectations.

1. Familiarity with open-source model monitoring, drift detection, or lineage tools (e.g., Evidently AI, Feast, LakeFS).

1. Hands-on experience serving models using KServe, Ray Serve, or Triton Inference Server.

1. Familiarity with enterprise security tools like Trivy, Aqua, or Snyk for code and container scanning.

1. Exposure to LLM/RAG architecture or GenAI platform integration.

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Contact:

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