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Artificial Intelligence​/Machine Learning Developer Security Clearance

Job in Ashburn, Loudoun County, Virginia, 22011, USA
Listing for: Unissant
Full Time position
Listed on 2026-06-03
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Artificial Intelligence/Machine Learning Developer with Security Clearance

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 an Artificial Intelligence/Machine Learning Developer to join our team and support our federal customer. Qualified applicants may be subject to a security investigation and must meet minimum qualifications for access to classified information. This is a highly technical position; individuals will be screened by peers in a technical review of skills and experience.

Essential Duties and Responsibilities
  • Drive a big data approach to execute government requirements to manage and enrich data to gather new insights.
  • Develop, train, and deploy advanced AI/ML and Gen-AI models.
  • Design and implement innovative AI solutions to address complex business challenges using techniques such as natural language processing and large language models.
  • Optimize model performance, ensuring accuracy, efficiency, and scalability.
  • Develop and maintain user‑friendly AI applications and interfaces, including chatbots, virtual assistants, and generative content tools.
  • Collaborate with cross‑functional teams to integrate AI solutions into existing systems and workflows.
  • Stay up to date with latest advancements in AI/ML and emerging technologies, such as generative AI and reinforcement learning.
  • Conduct research and experiments to explore new AI techniques and applications, including prompt engineering, Advanced RAGs, and fine‑tuning LLMs.
  • Ensure compliance with data privacy and security regulations, especially when dealing with sensitive data and generative AI outputs.
  • Brief technology partners, stakeholders, team members, and senior management on benefits and constraints of technology solutions.
Work Experience and

Job Skills
  • 3+ years of experience in the Information Technology field focusing on AI/ML engineering projects, MLOps and Dev Sec Ops  and technical architecture specifically.
  • Proficiency in developing, deploying, and fine‑tuning generative AI models, including large language models (LLMs).
  • Strong proficiency in programming languages such as Python, R, Java and C/C++ (optional).
  • Experience with machine learning and generative AI frameworks.
  • Experience with natural language processing techniques (e.g., text classification, language generation).
  • Solid understanding of cloud platforms (e.g.,
    AWS/Azure/GCP
    ) and deployment strategies.
  • Solid understanding of MLOps and Dev Sec Ops  practices for deploying AI‑ML models and applications.
  • Proficiency in front‑end development technologies (e.g., React, Angular, Vue.js, HTML, CSS, JavaScript).
  • Knowledge of database systems (e.g., SQL, No

    SQL, Vector Database, Graph Database) and data warehousing concepts.
  • Understanding and competency surrounding data storage, accesses, and loading.
  • Databases:
    Postgre

    SQL, No

    SQL, Vector Databases, Graph Databases, etc.
  • ETL/ELT Concepts.
  • Data warehouse concepts.
  • SQL.
  • Competency in data exploration, analytics, and feature engineering (Python specific).
  • Pandas / Num Py / Polars / PySpark.
  • Plotly / Matplotlib (some form of data visualization).
  • Data encoding / normalizing / regularizing / etc.
  • Deep learning concepts and architectures like CNNs, RNNs, LSTM, and GANs and ability to apply to real‑world data sets and problems.
  • ML modeling (Scikit-Learn, Tensor Flow, Keras, PyTorch).
  • NLP tools (Spa Cy, ThinC, Gensim).
  • Gen‑AI tools (Hugging Face models, OpenAI models, Grok).
  • General competency in various ML disciplines like Classification, Forecasting, Transformers, Generative, Anomaly Detection and Deep Learning.
Additional Qualifications
  • Enthusiastic, proactive, positive attitude with great listening skills, high integrity, and the ability to work effectively in a team environment.
  • Adaptability to changing priorities and a willingness to learn and grow.
  • Excellent organizational skills and the ability to manage…
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