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Machine Learning Manager Jobs in Washington, DC (NOW HIRING)

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

We are seeking a Machine Learning Engineer with a passion for building mission-critical ... Familiarity with distributed model training and GPU resource management. Physical Requirements

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Ability to collaborate in cross-functional teams (e.g., engineers, product managers) * Knowledge of ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$125 - $150/hr

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Ability to collaborate in cross-functional teams (e.g., engineers, product managers) * Knowledge of ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... Ability to collaborate in cross-functional teams (e.g., engineers, product managers) * Knowledge of ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Ability to collaborate in cross-functional teams (e.g., engineers, product managers) * Knowledge of ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site

$120K - $180K/yr

We are seeking a Machine Learning Engineer with a passion for building mission-critical ... Familiarity with distributed model training and GPU resource management. Physical Requirements

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$112K - $177K/yr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Work closely with product managers, developers, designers, and QA teams within a large Agile ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... management. Desired: * Experience with reviewing A.I. system architectures and data flows to ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... management. Desired: * Experience with reviewing A.I. system architectures and data flows to ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... management. Desired: * Experience with reviewing A.I. system architectures and data flows to ...

Aqua IT

Machine Learning Engineer

Springfield, VA · On-site

$125 - $150/hr

... source control management, continuous deployments, testing, and operational excellence * - 3+ years of machine learning/statistical modeling data analysis tools and techniques Preferred ...

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All JobsMachine Learning JobsMachine Learning Manager JobsMachine Learning Manager Jobs in Washington, DC

Machine Learning Manager information

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$92.5K

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How much do machine learning manager jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning manager in Washington, DC is $92,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,800.00 and $104,800.00 per year, depending on experience, location, and employer.

What is a machine learning manager?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.

What are the key skills and qualifications needed to thrive as a machine learning manager?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What are some of the main challenges a machine learning manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

Is machine learning a high paying job?

Machine Learning Managers typically earn high salaries due to their specialized skills in data analysis, programming, and model development. Compensation varies based on experience, location, and industry, but it is generally considered a well-paying role within the tech sector.

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

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

What are popular job titles related to Machine Learning Manager jobs in Washington, DC?

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

What job categories do people searching Machine Learning Manager jobs in Washington, DC look for?

The top searched job categories for Machine Learning Manager jobs in Washington, DC are:

Machine Learning Manager jobs near you
Infographic showing various Machine Learning Manager job openings in Washington, DC as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $92,543 per year, or $44.5 per hour.

Machine Learning Engineer

Chantilly, VA • On-site, Remote

NT Concepts
IT Services • 51 - 200 employees
Learn more about NT Conceptsexternal

Full-time

Posted 4 days ago

Job description

 

We are seeking a Machine Learning Engineer with a passion for building mission-critical capabilities to join our talent network. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, explore What's Next with us.

Mission Focus: Our machine learning teams bridge the gap between cutting-edge AI research and operational government missions. We are looking for engineers who can take machine learning and Computer Vision (CV) solutions from early research and prototyping all the way into stable, scalable production environments.

 

In this role, you will help design, build, and deploy automated ML workflows that directly support national security analysts and operators. We embrace modern agile practices, a DataOps/DevSecOps/MLOps ethos to "automate-first," and modern cloud-native architectures.

Clearance: Active TS/SCI required (CI Polygraph preferred or must be eligible to obtain)

Location/Flexibility: Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available)

Responsibilities 

  • Prototype to Production: Support the full machine learning lifecycle, taking computer vision models from experimentation and notebooks into containerized, high-throughput production microservices.
  • Mission Alignment: Work closely with mission partners, domain experts, and technical teams to understand real-world operational challenges and translate them into practical ML requirements.
  • MLOps & Pipeline Automation: Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring using modern tools (such as MLflow, Kubeflow, and GitLab CI/CD).
  • Model Development & Tuning: Train, fine-tune, and evaluate deep learning algorithms for computer vision tasks (e.g., object detection, classification, segmentation, tracking).
  • System Integration: Collaborate with cross-functional software engineers and cloud architects to integrate ML models cleanly into larger enterprise systems and secure cloud infrastructures.
  • Optimization & Governance: Optimize inference performance, apply secure coding practices, and monitor models for drift and reliability once deployed. 

 Qualifications

  • Clearance: Active TS/SCI clearance.
  • Hands-On Experience: Demonstrated professional experience developing, testing, and deploying machine learning models into real-world or production environments.
  • Deep Learning & CV: Strong programming skills in Python and hands-on experience with deep learning frameworks (primarily PyTorch, OpenCV, TensorFlow, or NumPy).
  • ML Lifecycle & MLOps: Practical familiarity with containerization (Docker, Kubernetes) and ML lifecycle/pipeline platforms (e.g., MLflow, Kubeflow, AWS SageMaker).
  • Cloud & DevOps Foundations: Familiarity working in cloud environments (AWS, Azure, or GCP) and modern development practices (Git, CI/CD pipelines, Agile methodologies).
  • Customer & Mission Mindset: Ability to understand the end-user's mission objectives, iterate based on user feedback, and clearly communicate technical approaches. 

Preferred / Desired Skills:

  • Experience working within secure, air-gapped, or classified cloud environments (e.g., AWS GovCloud / C2S).
  • Experience with synthetic data generation techniques or multi-modal models.
  • Exposure to Large Language Models (LLMs) or generative AI workflows.
  • Familiarity with distributed model training and GPU resource management. 

Physical Requirements

  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 10-15 pounds at times.

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