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Senior Data Engineer Job ID#: 25-1071 Clearance: Secret Location: Herndon, VA Who We Are Since our inception back in ...

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Selected role

251071: Senior AI ML Engineer Herndon VA

Navitas Business Consulting, Inc. Herndon, VA

Senior Full-time

Senior Data Engineer
Job ID#: 25-1071
Clearance: Secret
Location: Herndon, VA
Who We Are
Since our inception back in 2006, Navitas has grown to be an industry leader in the digital transformation space, and we’ve served as trusted advisors supporting our client base within the commercial, federal, and state and local markets.

What We Do
At our very core, we’re a group of problem solvers providing our award-winning technology solutions to drive digital acceleration for our customers! With proven solutions, award-winning technologies, and a team of expert problem solvers, Navitas has consistently empowered customers to use technology as a competitive advantage and deliver cutting-edge transformative solutions.

What You’ll Do
Navitas is seeking an advanced Senior ML Engineer with NLP to design, build, and deploy scalable AI/ML models for use within the DoD's Search Portfolio. This role requires a strong background in natural language processing, generative AI (LLMs, RAG), distributed computing, and cloud-native architecture. The successful candidate will collaborate with interdisciplinary teams and apply the latest advancements in AI research to deliver secure, mission-ready solutions that process and analyze massive datasets.

Responsibilities Will Include But Are Not Limited To

Design, develop, test, and support AI/ML pipelines on Databricks using Python to support a variety of Department of Defense (DoD) technical missions.
Develop and operationalize NLP solutions for large datasets using modern techniques such as context extraction, topic extraction, and keyword extraction (e.g., RAKE, TF-IDF, and other statistical or embedding-based methods).
Leverage advanced NLP libraries and frameworks including Spark NLP, Hugging Face, and TensorFlow to design and deploy scalable machine-learning models.
Build, train, and deploy GPU-based models optimized for performance and cost-efficiency across distributed compute environments (Apache Spark/Databricks/Kubernetes).
Apply MLOps best practices using MLflow for model lifecycle management, experiment tracking, and reproducibility.
Integrate AI capabilities with Elasticsearch and Neo4j to enhance search, graph analytics, and semantic understanding across enterprise datasets.
Collaborate with cross-functional teams of data scientists, software engineers, and mission stakeholders to integrate AI/ML capabilities across the Search Portfolio and other data products.
Manage the full lifecycle of AI/ML components, from research and model development through deployment, monitoring, and iterative improvement.
Diagnose and solve complex data challenges using analytical modeling, AI-driven reasoning, and modern informatics techniques.
Document and present technical design alternatives, trade-offs, and implementation strategies to technical and non-technical stakeholders.
Build and maintain shared ML tools, libraries, and reusable assets to accelerate innovation and ensure engineering consistency.
Support strategic AI roadmap development and architectural planning to enable rapid prototyping and experimentation with advanced AI capabilities.
Ensure compliance, security, and traceability in all AI/ML workflows and infrastructure aligned with DoD and federal standards.

What You’ll Need:

Bachelor’s degree with 5 years of relevant experience
5+ years of hands-on experience with Natural Language Processing (NLP), Large Language Models (LLMs), semantic search, text embedding, Retrieval-Augmented Generation (RAG), and generative AI applications.
Extensive knowledge of NLP techniques for large datasets, including context, topic, and keyword extraction methods.
Proficiency in NLP libraries and frameworks such as Spark NLP, Hugging Face, and TensorFlow.
4+ years of experience working in Databricks as an ML Engineer, including building and managing distributed ML pipelines.
Strong Python expertise, including experience developing Flask APIs and reusable ML utilities.
Experience with MLOps and MLflow for model tracking, deployment automation, and governance.
Hands-on experience developing and tuning GPU-based models in production environments.
Working knowledge of Elasticsearch and Neo4j preferred for search and graph-based AI applications.
Deep understanding of machine-learning subfields such as computer vision, reinforcement learning, and statistical learning theory.
Proven experience with data preprocessing, feature engineering, and model evaluation.
Proficiency with version control systems (e.g., Git) for collaborative ML development.
Demonstrated experience with Apache Spark or Databricks for distributed data and ML workloads.
Experience working with petabyte-scale datasets, data exploration, SQL, and visualization tools.

Equal Employer/Veterans/Disabled
Navitas Business Consulting is an affirmative action and equal opportunity employer. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Navitas Human Resources.
Navitas is an equal opportunity employer. We provide employment and opportunities for advancement, compensation, training, and growth according to individual merit, without regard to race, color, religion, sex (including pregnancy), national origin, sexual orientation, gender identity or expression, marital status, age, genetic information, disability, veteran-status veteran or military status, or any other characteristic protected under applicable Federal, state, or local law. Our goal is for each staff member to have the opportunity to grow to the limits of their abilities and to achieve personal and organizational objectives. We will support positive programs for equal treatment of all staff and full utilization of all qualified employees at all levels within Navitas.
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