ML Engineer (MSc. or PhD), Remote- Contract Remote (International)

Dover

India

Remote

INR 7,850,000 - 15,699,000

Full time

4 days ago
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Benefits offered by this job

Flexible hours
Global remote

Job summary

Dover is seeking a Senior ML Engineer (MSc or PhD) for a contract role—about 15 hours per week—and fully remote to support a global AI training project. You will develop and validate machine-learning models, training pipelines, inference systems, and supporting Python tooling.

The work is highly coding‑heavy, focusing on reproducible workflows, memory and throughput optimization, and rigorous testing to meet objective performance targets.

Qualifications

  • Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
  • Strong professional or research experience in machine learning.
  • Practical proficiency with Python and coding agents.

Responsibilities

  • Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
  • Implement model components, data pipelines, evaluation systems, and numerical methods.
  • Build reproducible programmatic workflows using Python and command-line tools.

Skills

Machine Learning

Education

Master’s degree or PhD in CS/ML/AI/Applied Math/Statistics/Engineering

Tools

Python

Job description

Role Title: Senior ML Engineer (MSc. or PhD)

Location: Global, fully remote

Job Type: Contract (~15 hours per week)

Schedule: Flexible-you choose the hours and days you work, including weekends if desired

Required Skills:

  • Machine Learning

We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python.

The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements.

This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow.

What You’ll Work On:
  • Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
  • Implement model components, data pipelines, evaluation systems, and numerical methods.
  • Build reproducible programmatic workflows using Python and command-line tools.
Required Qualifications:
  • A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
  • Strong professional or research experience in machine learning.
  • Practical proficiency with Python and coding agents.

Equivalent tools may also be considered when the candidate demonstrates directly relevant depth.

Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify.

Process:
  • Apply to the role and complete the screening questions.
  • Complete an AI interview of approximately 30 minutes.
  • Complete the hiring manager review.
Compensation Structure:

Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow. Minimum submission requirements apply.

Start Timeline & Availability:

Typically, roles are filled within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

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