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Mlops Engineer Remote Jobs in Reston, VA (NOW HIRING)

SAIC

Senior AI Systems Engineer

Chantilly, VA · On-site +1

$160K - $200K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Senior AI Systems ... Experience with DevOps practices, including MLOps, and CI/CD pipelines for AI/ML. * Strong ...

UnitedHealth Group

Senior Software Engineer

Washington, DC · On-site +1

$138K - $182K/yr

If not, open to remote outside of these areas. Primary Responsibilities: * Design, develop, test ... Familiarity with MLOps practices, model monitoring, versioning, and automated testing frameworks

ResolveSoft Inc

Be Seen First

Lead Technologist

Washington, DC · Remote

$110K - $130K/yr

Remote Travel: None Suitability / Background Investigation: Tier 1 (NACI) minimum to Tier 4 (High ... You will evaluate the existing CPU-only infrastructure, engineer GPU-enabled enhancements, lead a ...

VIVA USA INC

Data Engineer

MD · On-site +1

$114K - $137K/yr

Remote - onshore/near-shore (this means we expect the resource is remote and located outside of the ... Support AIOps/MLOps lifecycle workflows using MLflow for experiment tracking, model registry, and ...

SAIC

Senior Principal AI/ML Systems Engineer

Chantilly, VA · On-site +1

$160K - $200K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a highly skilled AI/ML ... Familiarity with DevOps practices, including MLOps, and CI/CD pipelines for AI/ML. * Must have ...

Edgesource

Data Engineer

Centreville, VA · On-site +1

$113K - $136K/yr

Understanding of machine learning workflows and MLOps concepts. Working at Edgesource: As an ISO ... Schedules (Remote / Hybrid) - - Medical / Dental / Vision / Flexible Spending Account (FSA ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and established 1099 options (no c2c ... MLOps, and emerging AI technologies. Candidates must live in the United States and be able to pass ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and established 1099 options (no c2c ... MLOps, and emerging AI technologies. Candidates must live in the United States and be able to pass ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and established 1099 options (no c2c ... MLOps, and emerging AI technologies. Candidates must live in the United States and be able to pass ...

kgs

FinOps Specialist (REMOTE)

Washington, DC · Remote

Collaborate with engineering, cloud architecture, and DevOps teams to identify and implement cost ... Establish and enforce AI development best practices, including MLOps, version control ...

kgs

FinOps Specialist (REMOTE)

Washington, DC · Remote

Collaborate with engineering, cloud architecture, and DevOps teams to identify and implement cost ... Establish and enforce AI development best practices, including MLOps, version control ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

... * We're remote - Work from wherever you want. We collaborate in real time on Slack or ... Proficiency with MLOps practices including experiment tracking, model versioning, and deployment

BAE Systems

Dir I- Data Eng

Falls Church, VA · On-site +1

$122K - $146K/yr

Establish engineering standards, integration patterns, and architectural guardrails for all ... Familiarity with responsible AI, governance frameworks, and MLOps practices. * Deep expertise in ...

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Mlops Engineer Remote information

See Reston, VA salary details

$39.5K

$120.5K

$199.2K

How much do mlops engineer remote jobs pay per year?

As of Sep 10, 2026, the average yearly pay for mlops engineer remote in Reston, VA is $120,540.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,300.00 and $157,600.00 per year, depending on experience, location, and employer.

What does an MLOps engineer do in a remote role?

An MLOps Engineer is responsible for streamlining and automating the deployment, monitoring, and management of machine learning models in production environments. Working remotely, they collaborate with data scientists, software engineers, and IT teams using cloud-based tools to ensure that ML models are scalable, reliable, and maintainable. Their tasks often include setting up CI/CD pipelines for ML workflows, managing model versioning, and monitoring model performance over time. Remote MLOps Engineers leverage communication and project management tools to stay aligned with distributed teams and ensure seamless operations.

What are common challenges faced by remote MLOps engineers, and how can they be addressed?

Remote MLOps Engineers often encounter challenges related to communication and collaboration, especially when coordinating with data scientists, developers, and operations teams across different time zones. To overcome these challenges, it's essential to establish clear documentation practices, utilize collaborative platforms for workflow management, and schedule regular virtual meetings to ensure alignment. Additionally, maintaining strong version control and automated CI/CD pipelines helps streamline model deployment and monitoring, reducing friction caused by remote coordination. Building proactive communication habits and leveraging cloud-based tools can significantly improve efficiency and team cohesion.

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

To thrive as an MLOps Engineer, you need a solid background in machine learning, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS or Azure, as well as certifications in cloud services or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills help you bridge the gap between data science and operations teams in a remote setting. These competencies are crucial for building scalable, reliable machine learning systems that deliver real-world value efficiently.

What is the difference between Mlops Engineer Remote vs Data Engineer?

AspectMlops Engineer RemoteData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; experience with cloud platforms and ML toolsBachelor's in CS, Data Engineering, or related; strong SQL and ETL skills
Work EnvironmentRemote, collaborative teams, cloud-based infrastructureRemote or on-site, data pipelines, cloud or on-premises systems
Industry UsageTech, AI, ML-focused companiesFinance, healthcare, tech, and other data-driven industries

While both roles involve working with data and cloud platforms, Mlops Engineers focus on deploying and maintaining machine learning models in production, often working remotely with ML-specific tools. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in cloud experience and data handling but differ in their core focus areas.

What are the most commonly searched types of Mlops Engineer jobs in Reston, VA?

The most popular types of Mlops Engineer jobs in Reston, VA are:

What are popular job titles related to Mlops Engineer Remote jobs in Reston, VA?

For Mlops Engineer Remote jobs in Reston, VA, the most frequently searched job titles are:

What job categories do people searching Mlops Engineer Remote jobs in Reston, VA look for?

The top searched job categories for Mlops Engineer Remote jobs in Reston, VA are:

What cities near Reston, VA are hiring for Mlops Engineer Remote jobs?

Cities near Reston, VA with the most Mlops Engineer Remote job openings:

Mlops Engineer Remote jobs near you
Infographic showing various Mlops Engineer Remote job openings in Reston, VA as of September 2026, with employment types broken down into 1% Internship, 90% Full Time, 5% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $120,540 per year, or $58 per hour.

Senior AI Systems Engineer

Chantilly, VA • On-site, Remote

SAIC
IT Services • 10K+ employees
Learn more about SAICexternal

$160K - $200K/yr

Full-time

Re-posted 13 days ago

Key responsibilities

  • Collaborate with cross functional teams to define AI/ML project goals, success criteria, and development roadmaps.

  • Understand and guide the design of advanced AI/ML models and algorithms to address mission challenges.

  • Support vendor teams in model validation and performance testing to ensure solutions meet mission requirements.

SAIC rating

7.6

Company rating: 7.6 out of 10

Based on 81 frontline employees who took The Breakroom Quiz

Job description

Job ID: 2612038

Location: Chantilly, VA, US

Date Posted: 2026-04-30

Category: Engineering and Sciences

Subcategory: Systems Engineer

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS.SCI_wPoly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE


Description

SAIC is seeking a Senior AI Systems Engineer to provide Systems Engineering and Technical Advisory (SETA) support to a mission critical program in Chantilly, VA. In this role, you will directly support the National Reconnaissance Office’s (NRO) Ground Enterprise Directorate (GED)—the organization responsible for architecting, acquiring, and sustaining the nation’s most advanced space and ground systems across their full lifecycle. 

Active Top Secret Clearance with Polygraph is required for this role.

As an Senior AI Systems Engineer, you will play a pivotal role in shaping the customer’s AI/ML strategy within a key ground segment. You will help drive innovation, guide technical direction, and ensure the delivery of cutting edge, mission aligned AI/ML capabilities. This position is ideal for engineers who thrive at the intersection of advanced analytics, system engineering, and strategic advisory work. 

Key Responsibilities to include:

  • Collaborate with cross functional teams to define AI/ML project goals, success criteria, and development roadmaps that align with mission priorities.
  • Understand and guide the design of advanced AI/ML models and algorithms, ensuring solutions effectively address complex mission challenges and deliver measurable value.
  • Translate mission and business challenges into AI/ML opportunities, clearly articulating benefits, risks, and tradeoffs to non-technical stakeholders.
  • Stay current on emerging AI/ML technologies, introducing best practices, tools, and methodologies to strengthen the customer’s technical posture.
  • Provide mentorship and technical leadership to junior AI/ML practitioners, fostering a culture of innovation and continuous learning.
  • Work closely with customer and vendor data engineers and architects to ensure data pipelines, infrastructure, and compute environments are optimized for model development and deployment.
  • Support vendor teams in rigorous model validation and performance testing, ensuring AI/ML solutions meet mission requirements for accuracy, reliability, and robustness.

Qualifications

Required Education and Experience:

  • Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience.
  • Active Top Secret Clearance with Polygraph.
  • 5+ years of industry experience in supporting AI/ML solutions.
  • Experience with cloud computing services (e.g., AWS, Azure, Google Cloud) and their AI/ML offerings.
  • Experience with ML frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R).
  • Experience with data modeling, data pipeline creation, and deployment of ML models in production environments.
  • Experience with DevOps practices, including MLOps, and CI/CD pipelines for AI/ML.
  • Strong analytical and problem-solving skills with the ability to work on complex issues where analysis of situations requires an in-depth evaluation of variable factors.
  • Excellent communication and interpersonal skills, with a proven record of engaging stakeholders and mentoring teams.

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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