Posted today
Top Secret/SCI
Unspecified
IT - Support
Reston, VA (On-Site/Office)
The Senior AI/Data Scientist supports mission-critical programs by designing, deploying, and operationalizing advanced AI and machine learning solutions in production environments. This role focuses on developing and enhancing LLM-based workflows—including RAG and agentic systems—while ensuring models are scalable, governed, and aligned with DoD standards across enterprise data and cloud platforms.
Security Clearance:
Active TS/SCI clearance required.
Minimum Requirements:
5+ years of experience in applied data science or machine learning roles with strong Python proficiency.
Demonstrated experience implementing NLP solutions and large language models (LLMs) in mission or enterprise environments.
5+ years of experience with data exploration, data cleansing, analysis, visualization, and data mining.
Experience supporting production-level ML systems, including data lake architectures and streaming platforms (e.g., Kafka, Accumulo, Solr, Elasticsearch).
Experience implementing end-to-end ML workflows, from data preparation through deployment, evaluation, and sustainment.
Hands-on experience with CI/CD pipelines supporting ML and data workflows.
Experience deploying and orchestrating ML services using container platforms such as Kubernetes.
Familiarity with modern orchestration and workflow tools (e.g., Airflow) and table formats such as Apache Iceberg.
Ability to rapidly learn and apply system and infrastructure concepts, including how ML pipelines integrate with enterprise data platforms.
Key Responsibilities:
Design, develop, and enhance AI/ML workflows, including Retrieval-Augmented Generation (RAG) and agentic architectures.
Fine-tune, evaluate, and validate ML and LLM models to meet mission performance, reliability, and compliance requirements.
Implement and enforce model governance, guardrails, and responsible AI controls across the ML lifecycle.
Deploy, monitor, and scale AI/ML solutions in production environments using CI/CD pipelines and Kubernetes orchestration.
Support streaming and search-centric data architectures leveraging platforms such as Kafka, Accumulo, Solr, and Elasticsearch.
Collaborate with data engineers, MLOps teams, and stakeholders to transition AI/ML capabilities from development to operational use.
Develop technical documentation and contribute to standards, best practices, and repeatable ML processes.
Troubleshoot complex issues across data ingestion, model performance, orchestration, and production pipelines.
Skills and Proficiencies:
Python-based ML development and evaluation.
NLP, LLMs, RAG pipelines, and agentic systems.
ML model fine-tuning, benchmarking, and performance analysis.
CI/CD pipelines for ML and data workflows.
Kubernetes-based deployment and orchestration.
Streaming, search, and analytics platforms (Kafka, Accumulo, Solr, Elasticsearch).
Modern data platforms and orchestration tools (Iceberg, Airflow).
Strong analytical, problem-solving, and technical communication skills.
Additional Information:
Nice-to-have experience with GPU-enabled platforms, Linux system administration, and ML hardware optimization.
Experience with MLOps frameworks and tooling (e.g., MLflow, Kubeflow) preferred.
Experience supporting classified, mission-critical, or large-scale government systems strongly preferred.
Security Clearance:
Active TS/SCI clearance required.
Minimum Requirements:
5+ years of experience in applied data science or machine learning roles with strong Python proficiency.
Demonstrated experience implementing NLP solutions and large language models (LLMs) in mission or enterprise environments.
5+ years of experience with data exploration, data cleansing, analysis, visualization, and data mining.
Experience supporting production-level ML systems, including data lake architectures and streaming platforms (e.g., Kafka, Accumulo, Solr, Elasticsearch).
Experience implementing end-to-end ML workflows, from data preparation through deployment, evaluation, and sustainment.
Hands-on experience with CI/CD pipelines supporting ML and data workflows.
Experience deploying and orchestrating ML services using container platforms such as Kubernetes.
Familiarity with modern orchestration and workflow tools (e.g., Airflow) and table formats such as Apache Iceberg.
Ability to rapidly learn and apply system and infrastructure concepts, including how ML pipelines integrate with enterprise data platforms.
Key Responsibilities:
Design, develop, and enhance AI/ML workflows, including Retrieval-Augmented Generation (RAG) and agentic architectures.
Fine-tune, evaluate, and validate ML and LLM models to meet mission performance, reliability, and compliance requirements.
Implement and enforce model governance, guardrails, and responsible AI controls across the ML lifecycle.
Deploy, monitor, and scale AI/ML solutions in production environments using CI/CD pipelines and Kubernetes orchestration.
Support streaming and search-centric data architectures leveraging platforms such as Kafka, Accumulo, Solr, and Elasticsearch.
Collaborate with data engineers, MLOps teams, and stakeholders to transition AI/ML capabilities from development to operational use.
Develop technical documentation and contribute to standards, best practices, and repeatable ML processes.
Troubleshoot complex issues across data ingestion, model performance, orchestration, and production pipelines.
Skills and Proficiencies:
Python-based ML development and evaluation.
NLP, LLMs, RAG pipelines, and agentic systems.
ML model fine-tuning, benchmarking, and performance analysis.
CI/CD pipelines for ML and data workflows.
Kubernetes-based deployment and orchestration.
Streaming, search, and analytics platforms (Kafka, Accumulo, Solr, Elasticsearch).
Modern data platforms and orchestration tools (Iceberg, Airflow).
Strong analytical, problem-solving, and technical communication skills.
Additional Information:
Nice-to-have experience with GPU-enabled platforms, Linux system administration, and ML hardware optimization.
Experience with MLOps frameworks and tooling (e.g., MLflow, Kubeflow) preferred.
Experience supporting classified, mission-critical, or large-scale government systems strongly preferred.
group id: 91137975
