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Machine Learning Engineer

Job in Ashburn, Loudoun County, Virginia, 22011, USA
Listing for: Unissant
Full Time position
Listed on 2026-08-08
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Engineering
Salary/Wage Range or Industry Benchmark: 110000 - 170000 USD Yearly USD 110000.00 170000.00 YEAR
Job Description & How to Apply Below

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at  .

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands‑on experience in machine learning, advanced analytics, and AI‑driven product development, with the ability to turn complex data into practical, mission‑focused solutions. This role is well suited for a technically strong professional who enjoys building and improving models, partnering across Agile teams, and supporting the delivery of innovative capabilities from early concept through deployment and ongoing performance optimization.

Essential Duties and Responsibilities:
  • Design, develop, and maintain machine learning models that support a variety of AI applications.
  • Analyze large and complex datasets to identify trends, test hypotheses, and generate actionable insights using statistical and analytical methods.
  • Build and support reliable data pipelines that improve data quality, accessibility, and usability for machine learning and analytics initiatives.
  • Collaborate with data engineering and cross‑functional teams to enhance data workflows and optimize supporting infrastructure.
  • Contribute to AI product development activities across the lifecycle, including prototyping, implementation, deployment, and post‑production support.
  • Monitor model effectiveness and product performance metrics, and perform ongoing enhancements to improve accuracy, scalability, and reliability.
  • Work closely with product managers, developers, designers, and QA teams within a large Agile development environment.
Work Experience and Job

Skills:
  • Three (3) to four (4) years of hands‑on experience in machine learning engineering, AI solution development, data analytics, or related technical work is preferred.
  • Experience supporting AI, machine learning, or advanced analytics initiatives is required.
  • Demonstrated experience developing and deploying AI/ML models in a production environment.
  • Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development.
  • Experience with machine learning libraries and frameworks such as Tensor Flow, PyTorch, or Scikit‑learn.
  • Familiarity with MLOps practices, CI/CD pipelines, and model deployment processes.
  • Working knowledge of SQL and No

    SQL databases and data processing tools such as Apache Spark or Hadoop.
  • Experience with analytics and visualization tools such as Tableau, Power BI, matplotlib, or Plotly.
  • Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related services is preferred.
  • Strong problem‑solving abilities, attention to detail, and organizational skills.
  • Ability to manage multiple assignments independently while collaborating effectively across technical and business teams.
  • Experience working in Agile product development environments is a plus.
Education:
  • Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related technical field is required.
  • Master's Degree in a relevant field is preferred.
  • Equivalent combination of education and experience may be considered in lieu of strict degree requirements, based on client standards.
Certificates, Licenses and Registrations:
  • Relevant certifications in cloud computing, machine learning, data science, or data engineering are a plus.
  • Additional technical certifications may be considered based on program requirements.
Communication

Skills:
  • Excellent verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non‑technical audiences.
  • Strong interpersonal skills and the ability to collaborate effectively across cross‑functional teams in a client‑facing environment.
Clearance Requirements:
  • Ability to obtain…
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