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

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Deployment & MLOps * Operationalize models with robust CI/CD workflows. * Deploy models usingMLflow ... Engineer high-quality features and maintain training/inference pipelines. Cloud and Platform ...

Leidos

Senior AI Platform Engineer

Adelphi, MD · On-site +1

$108K - $148K/yr

Remote, however must be within commuting distance of Adelphi, MD to report on site as needed ... Apply MLOps practices including model and prompt versioning, deployment gating, monitoring, and ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available) Responsibilities ... MLOps & Pipeline Automation : Build, maintain, and optimize robust pipelines for data preparation ...

ManTech

AI Engineer

Washington, DC · On-site +1

$141K - $236K/yr

Design, develop, and operationalize full-lifecycle AI/ML operations (MLOps/LLMOps). * Implement and ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

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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.

Machine Learning Engineer - Remote

Vienna, VA • On-site, Remote

Halvik
IT Services • 51 - 200 employees
Learn more about Halvikexternal

$140K - $150K/yr

Full-time

Re-posted 11 days ago

Job description

Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of something special!
Role and Responsibilities
Model Development
  • Collaborate with data scientists and SMEs to develop ML models using curated datasets.
  • Conduct experiments, prototypes, and proof-of-concepts to validate model performance.
  • Create scalable and reusable training pipelines using Databricks notebooks and MLflow.

Implementation and Optimisation
  • LLMs (Large Language Models), RAGs, and AI agent systems for various business applications. Deployment & MLOps
  • Operationalize models with robust CI/CD workflows.
  • Deploy models usingMLflow, SageMaker, or custom APIs.
  • Monitor production models for accuracy, drift, and latency; manage retraining schedules.

Data Integration & Architecture Alignment
  • Work closely with Data Engineering to align ML pipelines with the Bronze, Silver, Gold layers of a Medallion Architecture.
  • Engineer high-quality features and maintain training/inference pipelines.

Cloud and Platform Engineering
  • Leverage AWS services including S3, EC2, Lambda, SageMaker, and Step Functions.

Collaboration & Documentation
  • Document ML artifacts, processes, and performance outcomes.
  • Contribute to agile project ceremonies and maintain a feedback loop with stakeholders.
  • Share knowledge and mentor junior team members.

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, TensorFlow).
  • Proficient with Databricks, MLflow, and PySpark.
  • Solid understanding of model lifecycle and MLOps practices.
  • Experience with AWS-based data infrastructure and related DevOps practices.
  • Demonstrated ability to productionize models and integrate with business system
  • Strong understanding of mathematics and statistics relevant to machine learning and AI.
  • Proven experience with machine learning models and algorithms (supervised, unsupervised, deep learning, etc.).
  • Solid background in software engineering principles and best practices.
  • Hands-on experience with model training frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Experience with MLOps tools and workflows, particularly on AWS (SageMaker, Lambda, S3, etc.).
  • Practical experience with LLMs, RAGs, and AI agent architectures.
  • Proficiency with the Databricks platform for data engineering and ML pipelines.
  • Advanced programming skills in Python.
  • Excellent communication and teamwork abilities.

Preferred Skills:
  • Experience building and deploying interactive UIs for AI models using Streamlit, Gradio, or similar frameworks for rapid prototyping and real-time model interactions
  • Business acumen and ability to align AI solutions with organizational goals.
  • Optimize compute and storage resources for performance and cost-efficiency.

Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Halvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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