AI Research Scientist
Tasks
- Apply model evaluation benchmarking explainability security and responsible AI
- Apply prompt engineering model adaptation evaluation observability and governance for LLM systems
- Assess model architectures for regulated environments
- Build AI solutions using modern AI ML tools and frameworks
- Conduct original AI research and exploratory investigations
- Contribute to deployment and operationalization of AI solutions
- Develop and evaluate AI agents multi agent systems and workflows
- Develop and validate AI solutions lifecycle through deployment and monitoring
- Develop generative AI and RAG solutions
- Develop hypotheses design experiments evaluate results
- Monitor evaluate and experiment with emerging AI technologies
- Partner with software engineers platform teams and product managers to transition prototypes to production
- Provide technical guidance to peers and junior team members
- Rapidly prototype novel AI solutions
- Support innovation scalability security compliance and operational requirements
Perks/Benefits
- 401k employer match
- Adoption Assistance
- Dental insurance
- Disability insurance
- Health insurance
- Hybrid work schedule
- Life insurance
- Paid Holidays
- Paid vacation
- Parental leave
- Sick and Safe Leave
- Vision insurance
Skills/Tech-stack
Agent systems | Agentic Workflows | Benchmarking | Deep learning | Explainability | Fine Tuning | Generative AI | Governance | Hugging Face | Human-in-the-loop | Langchain | Langgraph | Language Models | Large Language Models | Machine Learning | Model Evaluation | Multi-Agent | Multi-Agent Systems | Neural Networks | Observability | Orchestration | Prompt engineering | PyTorch | Responsible AI | Retrieval-Augmented Generation | Security | The Loop | Transformer
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Regions
Countries
States
Cities
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