We are seeking a highly skilled and innovative Senior Data Scientist to join our advanced analytics and machine learning team. The ideal candidate will bring deep expertise across a range of AI/ML disciplines, including deep learning, classical machine learning, natural language processing (NLP), and Retrieval-Augmented Generation (RAG) with Large Language Models (LLMs). You will be responsible for building and deploying cutting-edge models that solve real-world problems in complex data environments.
Key Responsibilities:
- Lead development of predictive models using deep learning and classical machine learning algorithms.
- Build and optimize NLP models leveraging transformer-based architectures (e.g., BERT, GPT).
- Design and implement Retrieval-Augmented Generation (RAG) approaches for LLM-based applications.
- Work with vector databases and graph databases for knowledge representation and retrieval.
- Generate and use simulated data to support training and testing of ML models.
- Perform data standardization, aggregation, and integration from structured and unstructured sources.
- Collaborate with cross-functional teams to understand business needs and translate them into ML solutions.
- Document workflows, produce technical reports, and contribute to academic or industry publications.
- Use version control tools to manage collaborative model development (e.g., GitHub).
- Support end-to-end ML lifecycle from data wrangling and modeling to deployment and monitoring.
Required Qualifications:
- Minimum 8 years of hands-on experience in AI/ML software development using Python and R.
- Strong background in deep learning, transformer-based NLP, and classical ML.
- Experience with RAG, LLMs, and embedding-based retrieval systems.
- Expertise in data wrangling, data standardization, and feature engineering.
- Proven experience working with vector databases (e.g., FAISS, Pinecone, Weaviate) or graph databases (e.g., Neo4j).
- Strong understanding of ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Familiarity with version control systems (e.g., Git, GitHub).
- Experience with cloud computing platforms (AWS, GCP, or Azure).
- Demonstrated ability to produce high-quality technical documentation and research publications.
- Master’s degree or Ph.D. in Statistics, Computer Science, or a related quantitative discipline.
Preferred Qualifications:
- Hands-on experience with SAS, SQL, Amazon RDS, and JIRA.
- Knowledge of ML Ops practices and model deployment pipelines.
- Prior experience in contributing to academic or technical publications.
- Exposure to federal or enterprise-scale projects is a plus.
Job Types: Full-time, Contract
Pay: $160,000.00 - $175,000.00 per year
Benefits:
- 401(k)
- Dental insurance
- Health insurance
- Paid time off
- Vision insurance
Application Question(s):
- Are you eligible for a Public Trust?
Location:
- Reston, VA 20190 (Preferred)
Ability to Relocate:
- Reston, VA 20190: Relocate before starting work (Required)
Work Location: Hybrid remote in Reston, VA 20190