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BELTOConsulting

Careers

Machine Learning Engineer

Take models from notebook to production: data pipelines, evaluation, deployment and the monitoring that catches drift.

Machine Learning Engineer work environment
Division
BELTO Consulting
Seniority
Mid level
Location
Worldwide
Work mode
Remote
Type
Full-time
Compensation
$145,000–$190,000 per year
Deadline
Open until filled
Published
September 22, 2026
Status
Accepting applications

This is an active talent brief for work BELTO may staff as client demand and internal priorities require. Publication does not imply an existing team vacancy or a guaranteed hiring date.

This is a fully remote mid level role in BELTO Consulting. You will work with a distributed team on consequential client and internal priorities. The work combines hands-on delivery, architecture decisions, peer review, documentation and direct collaboration with commercial and delivery colleagues. We value clear reasoning, secure defaults and systems that remain understandable as they scale. Success means improving the quality and speed of decisions, leaving durable operating assets, and communicating trade-offs before they become surprises. The selection process includes a structured conversation and a practical, role-relevant exercise. We do not use protected personal characteristics in hiring decisions.

Responsibilities

  • Build training and inference pipelines that run reliably on a schedule, not by hand.
  • Define evaluation sets and metrics that reflect the client decision, not benchmark convenience.
  • Deploy models behind versioned interfaces with rollback.
  • Monitor drift, data quality and cost, and act before the client notices.
  • Document the limits of the model in language the client can act on.

Requirements

  • Production machine learning experience, including everything after model training.
  • Strong Python, plus containers and a cloud runtime.
  • Honest reasoning about evaluation and failure modes.
  • Ability to explain model behaviour to a non-technical decision maker.
  • Currently enrolled at, or holding a degree from, Stanford University or Harvard University.

Education eligibility

Applicants must be currently enrolled at, or hold a degree from, Stanford University or Harvard University. This is a BELTO hiring policy; neither university sponsors, endorses or partners in this recruitment.

Applicants must be currently enrolled at, or hold a degree from, Stanford University or Harvard University. This is an independent BELTO hiring policy; neither university sponsors, endorses or partners in this recruitment.

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