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Mlops Contract Jobs in Virginia (NOW HIRING)

Tetra Tech

Machine Learning Engineer - Remote

Vienna, VA · On-site

$150 - $200/hr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals ... Deployment & MLOps * Operationalize models with robust CI/CD workflows. * Deploy models usingMLflow ...

Saic

AI/ML Engineer

Chantilly, VA · On-site

$200 - $250/hr

... MLOps) requirements for rapid experimentation * Guide R&D experimentation framework and capability demonstration planning * Support experimentation support contract coordination with use case ...

Credence

Senior Google AI Engineer

Mclean, VA · On-site

$105K - $145K/yr

With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and ... Implement robust MLOps (experiment tracking, evaluation, bias/robustness testing, model versioning ...

Credence

Senior Google AI Engineer

Mclean, VA · On-site +1

$105K - $145K/yr

With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and ... Implement robust MLOps (experiment tracking, evaluation, bias/robustness testing, model versioning ...

Saransh Inc

AI Ops Engineer

Reston, VA · On-site

$72K - $97K/yr

Contract Required Skills: * AI/ML * Operations * Python * Langchain * AWS * Experience in AI Development, MLOps, or a similar role with a focus on AI/ML operations. * Proficiency in Python for ...

eSolutionsFirst, LLC

Databricks Architect

Mclean, VA · On-site

$66.50 - $87.25/hr

Databricks Architect 12 Months contract extension/ Fulltime job Vienna, VA About the Role * We are ... Partner with data science teams on MLflow, MLOps, machine learning, and GenAI/LLM workloads.

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals ... Deployment & MLOps * Operationalize models with robust CI/CD workflows. * Deploy models usingMLflow ...

SAIC

AI/ML Engineer

Chantilly, VA · Hybrid

$200K - $240K/yr

... MLOps) requirements for rapid experimentation * Guide R&D experimentation framework and capability demonstration planning * Support experimentation support contract coordination with use case ...

IntelliGenesis LLC

Senior AI Engineer

Reston, VA · On-site

$215K - $245K/yr

Architect and implement scalable MLOps pipelines for training, validation, and deployment * Deploy ... contract-specific affordability, organizational requirements and alignment with local market data.

IntelliGenesis

Senior AI Engineer

Reston, VA · On-site

Architect and implement scalable MLOps pipelines for training, validation, and deployment * Deploy ... contract-specific affordability, organizational requirements and alignment with local market data.

BTree Solutions, Inc.

AI ENGINEER

Reston, VA · On-site

USC, GC, H1B and EAD Contract Type: W2 * Develop and optimize machine learning and deep learning ... Experience with MLOps tools (e.g., MLflow, Kubeflow). * Knowledge of big data technologies (Spark ...

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Mlops Contract information

What is an MLOps contract?

An MLOps contract refers to a temporary or project-based agreement for professionals who specialize in Machine Learning Operations (MLOps). MLOps combines machine learning, software engineering, and DevOps practices to streamline the deployment, monitoring, and management of machine learning models in production. These contracts typically require expertise in automation, CI/CD pipelines, cloud platforms, and model lifecycle management. Contractors are often hired to help organizations quickly implement or scale their machine learning infrastructure, ensuring models are reliable, scalable, and secure.

What are some common challenges faced by MLOps contractors when integrating machine learning models into existing production systems?

MLOps contractors often encounter challenges such as aligning model deployment processes with an organization's existing infrastructure and ensuring seamless collaboration between data science and engineering teams. They must navigate differences in technology stacks, manage versioning of models and datasets, and address issues related to scalability and monitoring in production environments. Effective communication and a thorough understanding of both machine learning workflows and DevOps practices are key to overcoming these hurdles and delivering reliable, maintainable solutions.

What are the key skills and qualifications needed to thrive as an MLOps contract professional, and why are they important?

To thrive as an MLOps Contract professional, you need solid experience in machine learning, software engineering, and cloud infrastructure, often supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and platforms such as AWS, Azure, or GCP, along with certifications like AWS Certified Machine Learning or Google Professional ML Engineer, is highly valuable. Strong problem-solving, communication, and collaboration skills help you deliver robust solutions and work effectively with cross-functional teams. These skills ensure efficient deployment, scalability, and maintenance of machine learning models in production environments.

What is the difference between Mlops Contract vs Data Engineer?

AspectMlops ContractData Engineer
Required CredentialsCertifications in cloud platforms, scripting, and ML toolsDegree in Computer Science or related field, SQL, Python skills
Work EnvironmentProject-based, contract roles in cloud and ML teamsFull-time or contract, data pipeline development in data teams
Employer & Industry UsageTech companies, startups, consulting firmsLarge enterprises, finance, healthcare, tech
Search & Comparison IntentUnderstanding contract roles in ML operationsData pipeline and infrastructure roles

While both roles involve working with data and cloud tools, Mlops Contract focuses on deploying and maintaining machine learning models in production environments on a contractual basis. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in skills like scripting and cloud familiarity but differ in scope and responsibilities.

Is MLOps in high demand?

MLOps roles are in high demand due to the increasing adoption of machine learning and AI across industries. Professionals with skills in cloud platforms, automation, and tools like Docker, Kubernetes, and CI/CD pipelines are particularly sought after. The field offers strong job growth prospects and competitive salaries for qualified candidates.

What are the most commonly searched types of Mlops jobs in Virginia?

The most popular types of Mlops jobs in Virginia are:

What are popular job titles related to Mlops Contract jobs in Virginia?

For Mlops Contract jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Mlops Contract jobs in Virginia look for?

The top searched job categories for Mlops Contract jobs in Virginia are:

What cities in Virginia are hiring for Mlops Contract jobs?

Cities in Virginia with the most Mlops Contract job openings:

Mlops Contract jobs near you

Azure Data & MLOps Engineer

Xtreme Solutions, Inc

Petersburg, VA • On-site

$112K - $134K/yr

Contractor

Re-posted 2 days ago

Job description

Job Type
Contract
Description
CASCOM ESD Enterprise Analytics/AI Program
Schedule: Full-Time / 1.0 FTE
Work Arrangement: Primarily Remote with Required Travel to Fort Lee, VA
Clearance: Active Final Secret Required
The Opportunity
This role sits where data engineering, Azure integration, security, and production ML meet.
The Azure Data & MLOps Engineer will build the Azure data pipelines, integrations, deployment mechanisms, and MLOps foundation supporting enterprise dashboards, applications, and AI/ML models.
What You'll Do
  • Design data-ingestion and system-integration architecture.
  • Connect the analytics environment to authoritative Army systems.
  • Build and maintain production pipelines for ingestion, transformation, reconciliation, and synchronization.
  • Develop REST API, service, database, file-based, and event-driven integrations.
  • Support structured, semi-structured, and document-based data.
  • Establish model-development and deployment environments.
  • Implement CI/CD, versioning, model packaging, releases, rollback, and monitoring.
  • Deploy models as endpoints, containers, batch jobs, or integrated services.
  • Configure identity, secrets, logging, monitoring, alerting, and security controls.
  • Diagnose data latency, data quality, pipeline, model-endpoint, and integration failures.
  • Develop architecture diagrams, interface descriptions, data-flow diagrams, and operational procedures.
  • Support Power BI and Power Apps data connections.

Requirements
Must-Have Qualifications
  • Active final Secret clearance.
  • 6+ years of data engineering, cloud engineering, platform engineering, or software integration experience.
  • 3+ years using Microsoft Azure.
  • Hands-on Azure data-engineering experience.
  • Strong SQL and Python skills.
  • Experience building production ETL/ELT pipelines and API-based integrations.
  • Experience deploying or operationalizing machine-learning models.
  • Experience implementing identity, access, secrets, logging, and monitoring within cloud environments.
  • Production experience with at least two major Azure data technologies, such as:
    • Azure Data Factory
    • Azure Synapse Analytics
    • Azure Databricks
    • Azure SQL
    • Azure Data Lake Storage
    • Microsoft Fabric
  • Experience developing REST API, service, database, file-based, or event-driven integrations.
  • Experience with Git, Azure DevOps, or comparable CI/CD tooling.
  • Experience with data validation, schema management, error handling, logging, and recovery.
  • Bachelor's degree in computer science, information systems, engineering, data engineering, or related discipline; equivalent experience may substitute.
Strongly Preferred
  • Azure Government, cARMY, IL4/IL5/IL6, GCC High, or comparable restricted Government environments.
  • Azure Machine Learning, Azure OpenAI, MLflow, Docker, Kubernetes, or model-serving technologies.
  • Entra ID, managed identities, Key Vault, RBAC, private endpoints, network controls, and secure secrets management.
  • GCSS-Army, SAP, ERP, Army logistics, or DoD system integration.
  • Data lineage, metadata, governance, and architecture documentation.
  • Power BI gateways, semantic models, or Power Platform integration.
  • Classified-data support experience.

About Xtreme Solutions XSI is a leading provider of information technology and professional services known for outstanding service delivery in a wide range of professional services engagements around the country. Team XSI continually meets and exceeds customer expectations. We are passionate about our work and making a difference. Our vision is to be the best professional services management company for both our customers and our employees. We need employees that share this vision. Our remarkable employees are the key to our company's incredible success. XSI promotes a work environment of trust, integrity, respect, continual improvement, customer satisfaction, and business success. We strive to provide a competitive salary and benefits, an engaging and rewarding work environment, and training and development opportunities.
Equal Employment Opportunity Xtreme Solutions, Inc. is an Equal Opportunity Employer and federal contractor. All qualified applicants will receive consideration for employment without discrimination based on any status protected by applicable federal, state, or local law. As a federal contractor, Xtreme Solutions, Inc. takes affirmative action to employ and advance in employment qualified individuals with disabilities and protected veterans. We are committed to providing equal employment opportunities throughout all aspects of employment, including recruitment, hiring, promotion, compensation, training, and other terms and conditions of employment. Equal Opportunity Employer Individuals with Disabilities Protected Veterans

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