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Machine Learning Defense Jobs in Washington (NOW HIRING)

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... Understanding of Department of Defense requirements and standards is a plus

Machine Learning Engineer

Mclean, VA ยท On-site

$77.60K - $176K/yr

As a machine learning engineer on our defense technology team, you'll train, test, deploy, and maintain models that learn from data. In this role, you'll own and define the direction of mission ...

Machine Learning Engineer

Mclean, VA ยท On-site

$77.60K - $176K/yr

As a machine learning engineer on our defense technology team, you'll train, test, deploy, and maintain models that learn from data. In this role, you'll own and define the direction of mission ...

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Defense communities. We deliver end-to-end data and technology solutions that advance the ...

We are seeking a Machine Learning Engineer to join our team. Working at NT Concepts means that you ... Defense communities. We deliver end-to-end data and technology solutions that advance the ...

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Machine Learning Defense information

What are the key skills and qualifications needed to thrive as a Machine Learning Defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What are some common challenges faced by professionals in Machine Learning Defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.
What are popular job titles related to Machine Learning Defense jobs in Washington? For Machine Learning Defense jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Washington look for? The top searched job categories for Machine Learning Defense jobs in Washington are:
What cities in Washington are hiring for Machine Learning Defense jobs? Cities in Washington with the most Machine Learning Defense job openings:

Machine Learning (ML) Engineer

Velocity-X, LLC

Chantilly, VA โ€ข On-site

Full-time

Posted 18 days ago


Job description

About Velocity-X:
Velocity-X, a VelocityBlack company, constructs and deploys data management and analytics solutions for the defense and intelligence communities. Weโ€™re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your missionโ€™s biggest challenges.

Velocity-X is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.

Responsibilities:

  • Design, develop, and implement machine learning models and algorithms to solve specific business problems.
  • Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
  • Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
  • Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
  • Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
  • Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
  • Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
  • Troubleshoot and resolve issues related to machine learning models and pipelines.
  • Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
  • Contribute to the development of best practices and standards for machine learning development and deployment within the team.
  • Document machine learning models, experiments, and deployment processes.
  • Potentially work with large datasets and big data technologies.
  • Optimize machine learning models for performance and efficiency.

Qualifications:

  • Masterโ€™s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
  • Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
  • Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
  • Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).
  • Experience with data preprocessing, feature engineering, and data visualization techniques.
  • Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
  • Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
  • Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
  • Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.

Preferred Skills:

  • Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
  • Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
  • Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
  • Experience with building and deploying RESTful APIs.
  • Familiarity with big data technologies and distributed computing.
  • Experience with statistical modeling and inference.

Position Clearance Requirement:

TS/SCI with Full-Scope Polygraph

Equal Opportunity Employer:

Velocity-X is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.