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Machine Learning Engineer Python Jobs in North Carolina

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 ...

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 ...

Senior AI Machine Learning Engineer

Charlotte, NC ยท Hybrid

$119K - $157K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and ... Strong object oriented development experience using Python, Java, C# * Familiarity with big data ...

$110K - $140K/yr

Proficiency in at least one programming language (Java, Python or Scala) and a tried understanding ... Machine Learning applications. * You will develop data sets for POCs to demonstrate new insights.

AI Machine Learning Engineer

Charlotte, NC ยท Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... Python Exposure to with workflow automation platforms (Apache Airflow, Autosys, similar) Basic ...

AI/Machine Learning Engineer

Wilmington, NC ยท On-site

$82K - $112K/yr

Apply data science techniques, such as machine learning, statistical modeling, and artificial ... Demonstrated programming proficiency in Python and .NET/C# Education and Experience: Desired

Machine Learning & Operations Engineer

Durham, NC ยท Remote

$67K - $90K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale ... Experience with Python and ML frameworks (PyTorch, TensorFlow, or similar) * Experience building CI ...

Machine Learning & Operations Engineer

Durham, NC ยท Remote

$67K - $90K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale ... Experience with Python and ML frameworks (PyTorch, TensorFlow, or similar) * Experience building CI ...

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Machine Learning Engineer Python information

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.
What job categories do people searching Machine Learning Engineer Python jobs in North Carolina look for? The top searched job categories for Machine Learning Engineer Python jobs in North Carolina are:
What cities in North Carolina are hiring for Machine Learning Engineer Python jobs? Cities in North Carolina with the most Machine Learning Engineer Python job openings:
Infographic showing various Machine Learning Engineer Python job openings in North Carolina as of June 2026, with employment types broken down into 88% Full Time, 8% Part Time, 3% Contract, and 1% Nights. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer

Bespoke Labs

Boone, NC โ€ข On-site

Full-time

Posted 7 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 โ€” 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 โ€” 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 โ€” SFT, RLHF, PPO, DPO, or reward model training โ€” 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 โ€” held-out sets, benchmark design, avoiding train/eval contamination