Lead Data Scientist - NLP/LLM Fine-tuning
- $120,000 - $180,000
- Raleigh, NC
Join one of the Triangle’s most buzzworthy startups and put your LLM fine-tuning expertise to work shaping cutting-edge AI solutions!
A bit about us:
This is an opportunity to work on impactful AI projects, lead innovation in NLP/LLM fine-tuning, and shape the next generation of intelligent products. If you thrive in a collaborative, fast-paced environment and want to push the boundaries of AI, we’d love to hear from you.
Why join us?
- Competitive Base Salary
- Excellent health, dental and vision coverage
- Flexible Hours
- Very generous PTO
- Small team, autonomy
- Many more great perks!
Job Details
We are seeking a highly skilled Lead Data Scientist with expertise in Natural Language Processing (NLP) and Large Language Model (LLM) fine-tuning to drive innovation and deliver impactful AI solutions. In this role, you’ll lead the research, design, and implementation of cutting-edge NLP algorithms, develop advanced fine-tuning strategies for models like BERT, GPT, and their variants, and collaborate with cross-functional teams to integrate AI capabilities into real-world products and services. The ideal candidate has deep technical expertise in NLP, machine learning, and deep learning, along with a proven track record in fine-tuning LLMs for complex language tasks.
Key Responsibilities
Qualifications
Nice-to-Haves
Key Responsibilities
- Research, design, and implement advanced NLP algorithms with a focus on fine-tuning LLMs (BERT, GPT, etc.)
- Develop and apply custom fine-tuning strategies to optimize models for specific tasks and domains
- Collaborate with product, engineering, and analytics teams to integrate fine-tuned models into production environments
- Stay current with advancements in NLP, LLM architectures, and fine-tuning methodologies
- Analyze experimental results to guide decisions, improve performance, and scale solutions
- Mentor peers and share best practices for NLP modeling, experimentation, and deployment
- Drive innovation by exploring new experimentation methods and advanced statistical techniques
- Identify and address technology improvement opportunities through research and cross-team collaboration
Qualifications
- Master’s degree in Data Science, Statistics, Computer Science, or related field (PhD preferred)
- 6–8 years of professional experience, including at least 6 years in data science or analytics
- Strong background in NLP, deep learning, and machine learning, with hands-on LLM fine-tuning experience
- Proficiency in Python, TensorFlow, and PyTorch
- Experience with NLP libraries such as Hugging Face Transformers or AllenNLP
- Solid understanding of linguistics, semantics, and syntactic structures
- Proven ability to develop, test, and deploy models in production environments
- Familiarity with software engineering best practices (version control, testing, CI/CD)
- Strong communication and collaboration skills, with experience mentoring others
- Proven track record of delivering projects on tight deadlines
Nice-to-Haves
- PhD in a relevant field
- Experience with cloud platforms (AWS, Azure, GCP) and distributed computing environments
Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.
Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.