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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

VP of Research, Machine Learning

Charleston, WV · Remote

... engineering. * Set the technical bar for research rigor, judgment, and taste across the ... Requirements * Deep experience building or evolving real machine learning systems used in ...

3Pillar

Architect / Principal, AI ML Engineer

Charleston, WV · Remote

$160K - $200K/yr

Collaborate with leadership to align machine learning strategies with overall business objectives ... Master's degree in Computer Science, Engineering, Mathematics, or a related field with 15+ years of ...

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 ...

Experian

Analytics Engineer (Remote)

Charleston, WV · Remote

As the ideal candidate, you thrive at the intersection of data engineering, infrastructure, and machine learning, and care about the reliability, scalability, and usability of the platforms your ...

Lyra Health

VP of Data and AI

Charleston, WV · Remote

$251K - $346K/yr

Required Experience * 10+ years of progressive experience in AI, machine learning, data science, data engineering, or a related field, with 5+ years in a senior leadership role (Sr Director, VP) ...

Surescripts

Senior AI Engineer

Charleston, WV · Hybrid

$158K - $193K/yr

The Senior AI Engineer is a hands-on engineer who designs, builds, and ships AI and machine learning capabilities across Surescripts' platforms, applications, and systems. Working with product ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Charleston, WV

Machine Learning Engineer information

See Charleston, WV salary details

$30.6K

$125.1K

$188.1K

How much do machine learning engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Charleston, WV? The most popular types of Machine Learning Engineer jobs in Charleston, WV are:
What are popular job titles related to Machine Learning Engineer jobs in Charleston, WV? For Machine Learning Engineer jobs in Charleston, WV, the most frequently searched job titles are:
What cities near Charleston, WV are hiring for Machine Learning Engineer jobs? Cities near Charleston, WV with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Charleston, WV as of July 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote 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

Posted 28 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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