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Python Machine Learning Jobs in Washington (NOW HIRING)

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 · 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 ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

We are seeking a Machine Learning Engineer with a passion for building mission-critical ... Strong programming skills in Python and hands-on experience with deep learning frameworks ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development. * Experience with machine learning libraries and frameworks such as TensorFlow ...

UNISSANT

Machine Learning Engineer

Ashburn, VA · On-site

Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development. * Experience with machine learning libraries and frameworks such as TensorFlow ...

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How much do python machine learning jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for python machine learning in Washington is $66.39, according to ZipRecruiter salary data. Most workers in this role earn between $54.71 and $75.43 per hour, depending on experience, location, and employer.

What is a Python machine learning?

A Python Machine Learning job involves developing, training, and deploying machine learning models using Python. Professionals in this role work with libraries like TensorFlow, scikit-learn, and PyTorch to analyze data, build predictive models, and optimize algorithms. Responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models to production environments. These roles are commonly found in industries like finance, healthcare, and e-commerce, where data-driven decision-making is crucial.

What does a typical workday look like for a Python machine learning professional?

A typical workday for a Python Machine Learning professional often involves tasks like cleaning and pre-processing data, developing and training machine learning models, and evaluating their performance using statistical metrics. You'll collaborate with data engineers, data scientists, and product managers to understand business requirements and integrate models into production environments. Regularly, you'll participate in code reviews, team meetings, and troubleshooting sessions to optimize model performance and address any issues. This dynamic role requires both independent project work and frequent cross-functional collaboration to ensure that solutions meet real-world needs.

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

To thrive as a Python Machine Learning professional, you need a strong background in statistics, programming (especially Python), data analysis, and machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Proficiency in libraries and frameworks like scikit-learn, TensorFlow, PyTorch, and familiarity with data visualization and version control tools are highly valued, as are relevant certifications such as TensorFlow Developer or AWS Machine Learning. Strong problem-solving ability, effective communication, and teamwork skills are important for collaboration and translating technical findings to non-technical stakeholders. These competencies enable you to design, develop, and deploy robust machine learning models that drive business solutions and innovation.

What are the most commonly searched types of Python Machine Learning jobs in Washington?

The most popular types of Python Machine Learning jobs in Washington are:

What are popular job titles related to Python Machine Learning jobs in Washington?

For Python Machine Learning jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Python Machine Learning jobs in Washington look for?

The top searched job categories for Python Machine Learning jobs in Washington are:

Python Machine Learning jobs near you
Infographic showing various Python Machine Learning job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $138,100 per year, or $66.4 per hour.

Machine Learning Engineer

Washington, DC • On-site

AI Squared
See more jobs at AI Squaredexternal

Full-time

Re-posted 21 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.