Senior Data Scientist

We are seeking a highly skilled and innovative Senior AI/ML Engineer 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 6 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 MLOps 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 Type: Full-time

Pay: $160,000.00 - $175,000.00 per year

Benefits:

• 401(k)
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

Education:

• Master's (Preferred)

Experience:

• Python: 6 years (Required)
• R: 6 years (Required)
• Machine learning: 6 years (Required)
• Vector Database: 4 years (Required)
• AWS: 5 years (Required)
• SQL: 5 years (Required)

Work Location: In person