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Machine Learning Engineer Python Jobs in Fairfax, VA

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow. * Deep ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow. * Deep ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow. * Deep ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

Required : • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar ... Python; familiarity with ML frameworks such as PyTorch or TensorFlow. • Deep knowledge of ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

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Machine Learning Engineer Python information

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$23.5K

$143.1K

$207K

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

As of Jul 16, 2026, the average yearly pay for machine learning engineer python in Fairfax, VA is $143,074.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,900.00 and $168,100.00 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 is the salary of machine learning engineer in Python?

The average salary for a machine learning engineer proficient in Python typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those requiring specialized skills in deep learning or data engineering may offer higher compensation.

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 engineer makes $500,000 a year?

A senior or lead machine learning engineer with extensive experience, advanced skills in Python, deep learning, and data modeling can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Such roles often require advanced degrees, certifications, and a strong track record of successful projects.

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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI director, often involving advanced skills in Python, deep learning, and data science. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in competitive industries like tech or finance.

Is Python enough for ML engineers?

Python is a fundamental programming language for machine learning engineers due to its extensive libraries like TensorFlow, PyTorch, and scikit-learn. However, proficiency in data manipulation, algorithms, and understanding of machine learning concepts, along with knowledge of tools like SQL and cloud platforms, are also important for success in the role.
What are popular job titles related to Machine Learning Engineer Python jobs in Fairfax, VA? For Machine Learning Engineer Python jobs in Fairfax, VA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Fairfax, VA look for? The top searched job categories for Machine Learning Engineer Python jobs in Fairfax, VA are:
Machine Learning Engineer Python jobs near you
Machine Learning Engineer

Machine Learning Engineer

AI Squared

Washington, DC

Full-time

Re-posted 25 days ago

Job description

Machine Learning Engineer
Washington, DC (Hybrid)

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You'll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.

Key Responsibilities:
  • Design, implement, and maintain ML deployment pipelines for scalable production systems.
  • Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
  • Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
  • Partner with data scientists to transition models from research/prototype into production-ready deployments.
  • Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
  • Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
  • Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
  • Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
  • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proven experience deploying and maintaining machine learning models in production at scale.
  • Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
  • Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
  • Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
  • Strong understanding of MLOps best practices, monitoring, and automation.
  • Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
  • Strong communication and collaboration skills across technical and non-technical teams.