ML Ops Tech Lead Manager — Scale Data Science Platform

Veho; United States; On-site; USD 199,000 - 241,000; Full time

Benefits offered by this job

Equity package

Medical, dental, vision coverage

401(k) plan

Job summary

Veho is seeking a Technical Lead Manager for its Data Science Platform to shape a 1–2 year roadmap and embed engineers into key science projects. You will lead four engineers across ML infrastructure, ML operations, and embedded data science, driving AI tooling adoption and setting high technical standards.

You’ll collaborate with related teams to ensure scalable, production-ready ML services for forecasting, pricing, and routing, while maintaining velocity and impact for the business.

Qualifications

• ML platform experience: training and serving infrastructure, feature stores, orchestration, monitoring, deployment pipelines.
• Experience leading ML Platform / ML Ops teams in smaller scale companies.
• Experience driving AI/agentic tooling adoption inside an organization.
• Hands-on with open-source tooling for large-scale ML (e.g., Ray, Flink, Feast).

Responsibilities

• Lead and grow a team of four engineers spanning ML infrastructure, ML operations, and embedded data science project work.
• Improve internal ML platform, standardize infrastructure, deployments, and integration with systems.
• Set the roadmap for ML and Operations Research infrastructure.
• Embed engineers into major science initiatives to ensure technical soundness and knowledge transfer.
• Drive AI usage across Data Science; set standards and patterns for tooling adoption.
• Contribute to on-call rotation for data science production systems.

Skills

ML infra

ML Ops

Python

Cloud (AWS)

Data Warehouses

Collaboration

AI tooling adoption

Education

Bachelor’s Degree in a relevant field

Master’s Degree in a relevant field

Tools

Ray

Flink

Feast

AWS

Redshift

Databricks

Snowflake

Job description

Veho is seeking a Technical Lead Manager for its Data Science Platform to shape a 1–2 year roadmap and embed engineers into key science projects. You will lead four engineers across ML infrastructure, ML operations, and embedded data science, driving AI tooling adoption and setting high technical standards.

You’ll collaborate with related teams to ensure scalable, production-ready ML services for forecasting, pricing, and routing, while maintaining velocity and impact for the business.