Sr. Data Scientist

Location: Candidate local to Raleigh is strongly preferred (hybrid schedule 2x per week)

12+ months contract

PLEASE REVIEW IN DETAILS AS CANDIDATES WILL NEED TO HAVE THE FOLLOWING SKILLS (NO EXCEPTIONS):

- Master's or PhD Preferred!
- 5-10+ years of experience in AI and machine learning, model building and strong coding skills in python
- 2+ years of working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc. UTILIZING RAG!
- Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.
- Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination mitigation
- DevOps repos Debugging, building APIs and managing the algorithm flow across multiple workstreams in one repo
- Senior level experience deploying models in the Cloud (AWS) or Azure as secondary.

Nice to have: Candidate local to Raleigh is strongly preferred (hybrid schedule 2x per week)
- FANG Experience (Facebook, Amazon, Netflix, Google, or even Microsoft)

• Python Proficiency : Expert level of Python, with experience in writing efficient, clean, and modular code with ability to debug and test the new code thoroughly
• RAG Systems
  • Experience and deep understanding of Retrieval-Augmented Generation, including concepts like embedding-based search, document retrieval, and combining retrieved information with LLMs.
  • Hands-on experience with advanced RAG platform development and maintenance.

Familiarity with knowledge base creation, indexing, and retrieval pipelines.

• Knowledge of AI Architectures : Understanding of the end-to-end architecture of generative AI systems, including pre-processing, retrieval, ranking, and post-processing steps.

• Prompt Engineering
  • Expertise in crafting effective prompts for LLMs tailored to specific tasks
  • Experience with techniques like zero-shot, few-shot prompting, prompt tuning, and chain of thought.
• Content Generation
  • Understanding of generative AI applications in content creation, including best practices for producing accurate, coherent, and domain-specific outputs.
  • Ability to fine-tune components for custom use cases.
• Debugging and Performance Tuning
  • Skills in profiling and optimizing LLM responses for latency and accuracy.
  • Experience diagnosing issues in complex multi-component systems.

2. Monorepo and Collaboration Skills

• Working in Monorepo Environments
  • Experience managing and contributing to large, centralized codebases (monorepos).
  • Understanding of version control workflows suited for monorepos (e.g., Git-based branching strategies).
• Collaboration Tools and Practices
  • Proficient with CI/CD pipelines and tools like Jenkins, GitHub Actions, or GitLab CI.
  • Ability to work collaboratively with cross-functional teams in Agile settings.
  • Proficiency with code review practices and tools.

3. AI and NLP Knowledge

• NLP Expertise
  • Solid understanding of transformers, embeddings, and attention mechanisms.
  • Familiarity with techniques for handling domain-specific language models.

4. Complementary Skills

• Documentation and Communication
  • Ability to write clear technical documentation for processes, workflows, and API usage.
  • Strong communication skills for conveying technical insights to stakeholders.

Preferred Experience

• Previous experience working in legal tech or domain-specific generative AI use cases.
• Hands-on experience with deploying AI models in production at scale.
• Familiarity with multilingual generative AI and fine-tuning for specific language like French