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Remote Machine Learning Engineer Jobs in Aldie, VA

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

We are seeking a Machine Learning Engineer with a passion for building mission-critical ... Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available) Responsibilities

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch ...

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Remote Machine Learning Engineer information

See Aldie, VA salary details

$31.1K

$127.1K

$191K

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

As of Sep 9, 2026, the average yearly pay for remote machine learning engineer in Aldie, VA is $127,135.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

What is a remote machine learning engineer?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What are some typical challenges faced by remote machine learning engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

Are remote machine learning engineers still in demand?

Remote machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. Skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch are highly sought after, and many companies continue to hire for remote roles in this field.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for this role. The position typically involves tasks such as data analysis, model development, and collaboration through online tools, making remote work feasible with strong communication skills and proficiency in programming languages like Python or frameworks like TensorFlow. However, some roles may require occasional on-site meetings or access to specialized hardware.

What are the most commonly searched types of Machine Learning Engineer jobs in Aldie, VA?

The most popular types of Machine Learning Engineer jobs in Aldie, VA are:

What are popular job titles related to Remote Machine Learning Engineer jobs in Aldie, VA?

For Remote Machine Learning Engineer jobs in Aldie, VA, the most frequently searched job titles are:

What cities near Aldie, VA are hiring for Remote Machine Learning Engineer jobs?

Cities near Aldie, VA with the most Remote Machine Learning Engineer job openings:

Remote Machine Learning Engineer jobs near you
Infographic showing various Remote Machine Learning Engineer job openings in Aldie, VA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $127,135 per year, or $61.1 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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