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Contract Machine Learning Engineer Jobs in Charleston, WV

Bespoke Labs

Machine Learning Engineer

Charleston, WV · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bjak

Senior Machine Learning Engineer

Charleston, WV · Remote

$107K - $146K/yr

Role As a Senior Member of Technical Staff, Machine Learning, you are an independent owner of ... Collaborate closely with research, product, and engineering to deliver real user impact. * Mentor ...

Bjak

Staff Machine Learning Engineer

Charleston, WV · Remote

Role As Technical Lead, Machine Learning, you own the execution layer of A1's intelligence. You ... Collaborate closely with application engineering to integrate ML systems cleanly into backend ...

Bjak

Technical Lead, Machine Learning

Charleston, WV · Remote

Role As Technical Lead, Machine Learning, you own the execution layer of A1's intelligence. You ... Collaborate closely with application engineering to integrate ML systems cleanly into backend ...

Bjak

Applied AI Engineer

Charleston, WV · Remote

Role As an Applied AI Engineer, you will turn model capabilities into real product behavior. You ... This role sits at the intersection of machine learning, systems, and product, focusing on making AI ...

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Showing results 1-20

All JobsContract Machine Learning Engineer JobsContract Machine Learning Engineer Jobs in Charleston, WV

Contract Machine Learning Engineer information

See Charleston, WV salary details

$30.6K

$125.1K

$188.1K

How much do contract machine learning engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for contract machine learning engineer in Charleston, WV is $125,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $150,600.00 per year, depending on experience, location, and employer.

What is a contract machine learning engineer?

A Contract Machine Learning Engineer is a professional who builds and deploys machine learning models on a temporary or project-based basis. They typically work with companies seeking specialized expertise in data science, model development, or AI integration without committing to a full-time hire. Responsibilities may include data preprocessing, model training, algorithm optimization, and deployment. Contract roles allow for flexibility and are often remote, making them ideal for businesses with short-term AI needs or startups looking to scale their machine learning capabilities quickly.

What are the typical day-to-day responsibilities of a contract machine learning engineer?

As a Contract Machine Learning Engineer, your daily tasks usually involve gathering and preprocessing data, building and fine-tuning machine learning models, and collaborating with software engineers and product managers to integrate your models into production systems. You may also meet with clients or internal teams to gather requirements and provide technical insights, as well as document and present your findings to stakeholders. Work is typically project-based and may require a high degree of independence, flexibility, and adaptability. This dynamic environment often exposes you to a variety of industries and technical challenges, making each project unique and providing valuable experience for professional growth.

What are the key skills and qualifications needed to thrive in the contract machine learning engineer position, and why are they important?

To thrive as a Contract Machine Learning Engineer, you need a strong background in machine learning algorithms, data preprocessing, statistical analysis, and proficiency in programming languages such as Python or R, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms (AWS, Google Cloud, Azure) or certifications in these areas are common requirements. Excellent problem-solving, communication, and time management skills are vital, especially when working with cross-functional teams and managing multiple projects remotely. These skills ensure effective delivery of high-quality, scalable machine learning solutions within tight project timelines and diverse client environments.

What are popular job titles related to Contract Machine Learning Engineer jobs in Charleston, WV? For Contract Machine Learning Engineer jobs in Charleston, WV, the most frequently searched job titles are:
What cities near Charleston, WV are hiring for Contract Machine Learning Engineer jobs? Cities near Charleston, WV with the most Contract Machine Learning Engineer job openings:
Contract Machine Learning Engineer jobs near you
Infographic showing various Contract Machine Learning Engineer job openings in Charleston, WV as of June 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $125,147 per year, or $60.2 per hour.

Machine Learning Engineer

Bespoke Labs

Charleston, WV • On-site

Full-time

Re-posted 19 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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