Hi , Job title Senior AI/ML Engineer Location : Hybrid (Herndon, VA) Duration- : 6+ months contract About the Role We're seeking an experienced Senior Data Engineer / Machine Learning Engineer with a strong background in Natural Language Processing (NLP) and AI/ML systems to design, build, and deploy scalable solutions supporting Department of Defense (DoD) data missions. This role involves applying cutting-edge techniques in large language models (LLMs) , retrieval-augmented generation (RAG) , semantic search , and distributed data processing to deliver secure, production-grade AI capabilities. You'll collaborate closely with cross-functional teams to operationalize advanced ML systems that transform how large-scale data is processed, analyzed, and understood. Key Responsibilities Design, develop, test, and maintain scalable AI/ML pipelines using Python and Databricks to support diverse DoD technical missions. Build and deploy NLP solutions leveraging context extraction, topic modeling, and embedding-based methods (e.g., RAKE, TF-IDF, word/sentence embeddings). Develop and operationalize GPU-accelerated ML models across distributed environments (Spark, Databricks, Kubernetes). Utilize libraries and frameworks such as Spark NLP , Hugging Face , and TensorFlow to build and refine production-ready models. Implement MLOps practices with MLflow for model lifecycle management, versioning, and reproducibility. Integrate AI and ML solutions with Elasticsearch and Neo4j to enable semantic search, graph analytics, and knowledge discovery. Collaborate with software engineers, data scientists, and mission stakeholders to deliver robust, scalable AI capabilities. Drive innovation by contributing to shared ML tools, frameworks, and best practices across teams. Ensure compliance, traceability, and data security in all AI/ML workflows in alignment with federal standards. Support strategic planning and R&D for emerging AI/ML capabilities and infrastructure design. Required Qualifications Bachelor's degree in Computer Science, Engineering, or a related field. 5+ years of experience in data engineering, ML engineering, or AI-focused roles . Proven expertise in NLP , LLMs , semantic search , text embeddings , and generative AI . Strong proficiency in Python , including experience with Flask APIs and reusable ML utilities. Hands-on experience with Databricks , Apache Spark , and distributed data processing. Deep familiarity with MLOps , including MLflow for tracking, deployment, and automation. Experience developing and optimizing GPU-based models in production environments. Working knowledge of Elasticsearch and Neo4j (preferred). Solid understanding of data preprocessing , feature engineering , and model evaluation at scale. Proficiency with Git and collaborative development workflows. Experience working with large-scale datasets and strong command of SQL and data visualization tools. Nice to Have Exposure to federal data environments or defense-related missions . Knowledge of additional ML subfields such as computer vision, reinforcement learning, or advanced statistical modeling. Experience architecting secure, cloud-native ML systems using AWS, Azure, or Google Cloud Platform. Best Regards, Atul Singh Sr. Technical Recruiter || Talent Portus Email:
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