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Contract Meta Machine Learning Jobs in Virginia (NOW HIRING)

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site

$140K - $150K/yr

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 ...

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 delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Niyam IT, Inc.

AI Machine Learning Engineer

Ashburn, VA · On-site

This position is contingent upon award of contract. Roles and Responsibilities * Design, develop, train, and validate advanced AI and machine learning models to support mission-critical use cases for ...

Niyam IT, Inc.

AI Machine Learning Engineer

Ashburn, VA · On-site +1

This position is contingent upon award of contract. Roles and Responsibilities * Design, develop, train, and validate advanced AI and machine learning models to support mission-critical use cases for ...

Meta

Network Engineer, Optical Deployment

Reston, VA

$162K/yr

Manage key vendor relationships including contract negotiations, pricing, and evaluation of current ... Please note that Meta may leverage artificial intelligence and machine learning technologies in ...

RIVIDIUM

AI / Machine Learning Lead

Alexandria, VA · Hybrid

This position is contingent upon contract award. Key Responsibilities * Lead AI and machine learning initiatives that support modernization, automation, and advanced analytics objectives. * Build or ...

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Contract Meta Machine Learning information

What are the key skills and qualifications needed to thrive as a Contract Meta Machine Learning Engineer, and why are they important?

To thrive as a Contract Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and advanced machine learning concepts, often supported by a relevant degree or equivalent experience. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and version control systems is essential, along with experience in meta-learning techniques. Strong analytical thinking, problem-solving abilities, and effective communication skills help you design innovative solutions and collaborate with diverse teams. These competencies are crucial to efficiently develop, implement, and optimize meta-learning models that address complex, evolving business challenges.

What is the difference between Contract Meta Machine Learning vs Contract Data Scientist?

AspectContract Meta Machine LearningContract Data Scientist
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; experience with machine learning frameworksMaster's or PhD in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentFocus on developing and deploying machine learning models, often in AI projectsData analysis, modeling, and interpretation to inform business decisions
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, and tech firms

Contract Meta Machine Learning roles primarily focus on building and deploying machine learning models, often requiring advanced technical skills in AI. Contract Data Scientist positions involve analyzing data, creating models, and deriving insights for business strategies. While both roles require strong analytical skills and similar educational backgrounds, Meta Machine Learning roles are more specialized in AI development, whereas Data Scientist roles emphasize data analysis and interpretation.

What are some of the unique challenges faced by contract machine learning engineers at Meta, and how can candidates prepare for them?

Contract machine learning engineers at Meta often work on high-impact projects with tight deadlines and rapidly evolving requirements. One of the main challenges is quickly integrating into existing teams and understanding Meta's large-scale data infrastructure and proprietary tools. To prepare, candidates should familiarize themselves with Meta's open-source frameworks, practice adapting to new codebases, and be ready to communicate effectively with cross-functional stakeholders. Building strong collaboration skills and maintaining flexibility will help contract engineers deliver value efficiently in this fast-paced environment.

What are Contract Meta Machine Learning professionals?

Contract Meta Machine Learning professionals are specialists hired on a contractual basis to design, develop, and optimize machine learning models, often focusing on meta-learning techniques. Meta-learning, sometimes called 'learning to learn,' involves creating algorithms that can adapt to new tasks with minimal data or retraining. These professionals typically work with organizations to solve complex, data-driven problems, leveraging advanced AI techniques for efficiency and scalability. They may also help integrate these solutions into existing systems and provide guidance on best practices for model deployment.
What are the most commonly searched types of Meta Machine Learning jobs in Virginia? The most popular types of Meta Machine Learning jobs in Virginia are:
What are popular job titles related to Contract Meta Machine Learning jobs in Virginia? For Contract Meta Machine Learning jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Contract Meta Machine Learning jobs in Virginia look for? The top searched job categories for Contract Meta Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Contract Meta Machine Learning jobs? Cities in Virginia with the most Contract Meta Machine Learning job openings:
Contract Meta Machine Learning jobs near you
Machine Learning Engineer - Remote

Machine Learning Engineer - Remote

Halvik

Vienna, VA • On-site

$140K - $150K/yr

Full-time

Posted 20 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.