Note: The job is a remote job and is open to candidates in USA. Sapience AI is a collective intelligence platform for professional communities that turns expertise scattered across CRMs, AMS platforms, and knowledge bases into searchable, actionable knowledge. The Foundational Model Research Data Scientist will design experiments, adapt and evaluate foundational models, improve grounding and trust, and translate research advances into dependable capabilities for the COGENT architecture and MINERVA platform.
Responsibilities
- Design and run experiments on foundational models relevant to collective intelligence
- Investigate how models understand language, ground answers, and reason over knowledge
- Turn open questions into experiments with clear hypotheses and honest results
- Adapt foundational models to the language and needs of professional communities, including fine-tuning and alignment where it helps
- Improve grounding and reduce confident errors in domain settings
- Balance capability against cost, latency, and the constraints of production
- Build rigorous evaluation for what matters here: accuracy, groundedness, safety, and trust
- Design evaluations that reflect real community needs, not just public benchmarks
- Keep the organization honest about what a model can and cannot do
- Partner with data engineering on the datasets that training and evaluation depend on
- Handle data thoughtfully, including quality, bias, and protection of sensitive community knowledge
- Build the evidence base that makes model claims defensible
- Feed model advances into the neuro-symbolic COGENT architecture, and study how neural and symbolic methods work together
- Help decide where a foundational model belongs and where structure should carry the load
- Turn research into behavior the platform can rely on
- Track the fast-moving foundational model field and separate real progress from hype
- Bring in advances that matter and set aside those that do not
- Share knowledge so the whole organization stays current
- Study and reduce the failure modes that erode trust, including hallucination and bias
- Build toward models whose answers members can trust and trace
- Treat safety and trust as part of the research, not a later concern
Skills
- A strong research background in machine learning, NLP, or a related field, with a graduate degree or equivalent experience
- Hands-on experience with foundational models and modern LLMs, including training, fine-tuning, or evaluation
- Rigor in experiment design, evaluation, and honest interpretation of results
- Strong Python and modern ML frameworks
- The ability to turn research into advances a product can use
- Care for safety, bias, and trust in model behavior
- Clear written communication of technical findings
- Foundational model research, fine-tuning, and alignment
- Evaluation design for accuracy, groundedness, and safety
- Experiment design and rigorous analysis
- Grounding and retrieval-augmented methods
- Working with sensitive data responsibly
- Translating research into product-ready advances
- Clear technical writing and communication
- PyTorch or equivalent deep-learning frameworks
- LLM training, fine-tuning, and serving tooling
- Experiment tracking and evaluation frameworks
- Retrieval, embeddings, and vector systems
- Distributed training and cloud or GPU environments
- Python as the primary language, plus data and analysis tooling
- Integration with the COGENT architecture and the MINERVA platform (trained on the job)
- Prior research or applied science work on foundational models, LLMs, or NLP
- A track record of experiments that led to real advances or sound decisions
- Experience bridging research and engineering
- Publications, patents, or shipped systems in foundational models or applied NLP
- Experience with retrieval-augmented generation and grounding
- Familiarity with neuro-symbolic methods and knowledge graphs
- Experience adapting models to specialized domains
- Experience handling sensitive or regulated data responsibly
- Industry research experience in a fast-moving AI setting is a plus
Benefits
- Early stage equity
- Generous health and wellness benefits
Company Overview