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Machine Learning Engineer Python Jobs in Durham, NC

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to ...

Machine Learning Tutor

Raleigh, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to ...

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Machine Learning Engineer Python information

See Durham, NC salary details

$22.2K

$135.3K

$195.7K

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

As of Jun 25, 2026, the average yearly pay for machine learning engineer python in Durham, NC is $135,255.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,800.00 and $159,000.00 per year, depending on experience, location, and employer.

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 are popular job titles related to Machine Learning Engineer Python jobs in Durham, NC? For Machine Learning Engineer Python jobs in Durham, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Durham, NC look for? The top searched job categories for Machine Learning Engineer Python jobs in Durham, NC are:
Infographic showing various Machine Learning Engineer Python job openings in Durham, NC as of June 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $135,255 per year, or $65 per hour.

Machine Learning Engineer Lead

LexisNexis

Raleigh, NC • On-site

$115K - $192K/yr

Full-time

Posted 14 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

150th of 429 rated business services


Job description

About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role
Do you love collaborating with teams to solve complex technical problems?
We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This role combines deep ML expertise with distributed systems engineering and AI platform development.
In this role you will be a hands-on engineer and leader that will lead a high-performing team of 4-5 ML engineers, drive platform-level decisions, and ensure enterprise-grade scalability, reliability, and responsible AI compliance.
Responsibilities:
  • Lead, mentor, and grow a team of 4-5 ML engineers.
  • Provide architectural direction and code-level guidance.
  • Establish engineering best practices for ML system design, testing, and deployment.
  • Conduct design reviews, performance reviews, and technical roadmap planning.
  • Architect distributed ML systems serving multiple global products.
  • Standardize infrastructure patterns for LLM serving and retrieval systems.
  • Define and implement enterprise-ready agentic frameworks.
  • Architect multi-step reasoning systems.
  • Lead decisions on deterministic workflows vs. autonomous agents.
  • Implement guardrails, safety layers, and traceability mechanisms.
  • Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
  • Establish CI/CD standards for ML lifecycle management.
  • Ensure compliance with enterprise data governance and responsible AI standards.

Requirements
  • 8-10 years of Machine Learning/Software Engineer experience
  • 2-3 years of people management experience.
  • Master's degree or bachelor's degree, computer science degree is highly desirable.
  • Strong software engineering background with experience in building system design, architecting AI feature/products that caters large number of users and deals with large volume of unstructured data
  • Experience with ML deployment to production
U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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