Join Kforce's client's cutting-edge Data Science and Machine Learning Capability Center (CC) within the Information, Data and Analytics (IDA) team in Houston, TX. This role is part of a high-impact innovation program in collaboration with NVIDIA, focusing on scalable HPC-AI applications, with a direct tie to business-critical scientific computing (e.g., seismic imaging).
Summary:As a Senior Data Scientist, you'll drive the development, deployment, and lifecycle management of production-grade AI/ML solutions. You'll work on full-stack data science tools and multimodal LLMs, with the infrastructure to scale-from on-prem HPC compute to cloud burst capacity.
About the Project:This position supports the innovation initiative under the GenAI R&D and HPC Program. The goal is to deepen the client's competitive edge in AI-driven scientific computing by developing scalable models and tools that accelerate R&D workflows and insights.
The role is funded through a multi-year investment in:
- On-premises and cloud-based HPC compute infrastructure
- High-performance storage and toolsets
- Dedicated AI/ML staffing to deliver next-generation digital solution
Key Responsibilities:
- Design, develop, and operationalize advanced AI/ML models, especially in deep learning, reinforcement learning, and multimodal LLMs
- Build full-stack data science applications deployed at scale across digital platforms
- Convert R&D prototypes into scalable, production-ready solutions
- Collaborate with research and engineering teams to deliver impactful GenAI tools and models
- Adhere to software quality, digital assurance, and MCDS quality initiative standards (health checks, code reviews, audits)
- Evaluate new data science opportunities and contribute to internal communities of excellence (CoEs, CoPs)* Ph.D. (preferred) or Master's degree in a STEM field
- Mastery in Machine Learning, Statistical Modeling, and Exploratory Data Analysis
- Deep expertise in Deep Learning and Reinforcement Learning
- Proficient in PyTorch or TensorFlow
- Strong core programming skills (e.g., Python)
- Knowledge of AI Engineering essentials, DevOps, and Agile methodologies
- Hands-on experience with cloud deployment frameworks and infrastructure/tooling (e.g., Azure, AWS, or GCP)
Bonus Skills (Nice-to-Have):
- Exposure to HPC Compute and Storage, Scientific Data Tools
- Expected to convert R&D prototypes into production-ready tools
- Must demonstrate strong ML/AI technical mastery and the ability to work cross-functionally with the company's scientific research and engineering teams
- Familiarity with Information Management, Data Governance, and Value Mapping
- Understanding of regulatory and compliance frameworks
- Experience collaborating with external research partners or vendors (e.g., NVIDIA)
What You'll Gain:
- Opportunity to work with cutting-edge AI research and global innovation leaders
- Exposure to real-world scientific and engineering challenges in energy exploration
- A collaborative, intellectually rich environment with support for continuous learning
- Ability to shape scalable digital products with industry impact