AI/ML Engineer (Model Validation & Training)

Excellent Part-time consulting opportunity with the possibility of FTE // Professional Experience validating accuracy and training the models required!

This Jobot Consulting Job is hosted by: Craig Rosecrans

Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.

Salary: $40 - $65 per hour

A bit about us:

We are partnering with a global digital transformation team supporting next-generation AI initiatives for a major enterprise technology program. This role will work directly alongside a senior AI architect helping validate model accuracy, support training workflows, and contribute to the development and refinement of production-bound machine learning solutions.

This is an excellent opportunity for an early-career AI/ML engineer to gain hands-on experience with real-world model evaluation, LLM development workflows, and enterprise-scale applied AI systems.

Why join us?

Part-time contract (~20 hours per week)

Fully remote

Flexible scheduling

Opportunity to contribute to high-visibility enterprise AI development initiatives

Job Details

Responsibilities

Support evaluation and validation of machine learning and LLM outputs for accuracy, consistency, and reliability

Assist with training dataset preparation, labeling, and refinement

Contribute to prompt engineering experimentation and response testing

Help monitor model performance and recommend improvements

Collaborate with senior engineers on iterative model tuning and deployment readiness

Document workflows, testing results, and evaluation methodologies

Participate in ongoing experimentation supporting production AI solutions

Required Qualifications

1-3 years of experience in Machine Learning, AI engineering, or applied data science

Hands-on experience with Python for ML workflows

Familiarity with LLM ecosystems (OpenAI, Gemini, Claude, or similar)

Experience working with structured and unstructured datasets

Exposure to model validation, testing pipelines, or evaluation frameworks

Strong attention to detail and analytical problem-solving skills

Ability to work independently in a distributed engineering environment

Preferred Qualifications

Experience supporting prompt engineering or RAG-style workflows

Exposure to model fine-tuning or dataset optimization techniques

Familiarity with evaluation tooling for LLM accuracy and hallucination detection

Experience working alongside senior architects or research teams

Background supporting enterprise AI initiatives or production-bound experimentation

Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.

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