Company Description
Daice Labs is building hybrid AI frameworks that integrate today's models into systems that learn continuously. Founded by MIT CSAIL scientists, we focus on building new architectures by combining LLMs/DL with symbolic reasoning and bio-inspired system design. Operating on two tracks, our Product Lab develops industry-specific solutions for collaborative human teams + AI co-building and co-owning vertical applications, while our Research Lab explores how principles of natural intelligence can guide systems design of new hybrid AI architectures.
Join us in taking the next leap in productivity through collaborative innovation.
Role Description
This is a full-time remote role for an Applied AI Engineer. The Applied AI Engineer will be responsible for developing and deploying AI models, participating in the design of hybrid AI frameworks, and conducting research on integrating symbolic reasoning with LLMs and DL. Day-to-day tasks include pipeline development, software development, deploying, evaluation and testing of hybrid frameworks. The role involves both independent work and collaboration with cross-functional teams to drive the evolution of AI systems.
Qualifications
- Strong foundation in Pattern Recognition and Computer Science
- Experience with Neural Networks and Natural Language Processing (NLP)
- Proficiency in Computer Science and ML Algorithms (proficiency in python and ML stack languages)
- Experience with Statistics
- Proficient in Software Development
- Excellent problem-solving skills and ability to work both independently and in collaborative environments
- Bachelor degree and preferable advanced degree (Master's or PhD) in Artificial Intelligence, Computer Science, or related fields
- Experience with hybrid AI frameworks and symbolic reasoning
- Understanding of bio-inspired system design and adaptability principles
- Experience building ML platforms/dev‑tools; you’ve developed agentic systems, sandboxes, or orchestration systems
- Strong in frameworks including both TypeScript + Python (Go a plus); API design, JSON Schema; function calling, tool use, memroy and embedding.
- Experience in Containers and quotas
- Experience in Observability, Postgres, Redis; message queues
- Experience in Evaluation; you’ve built golden sets, regressions, drift detection, and gates for ML/agents
- Experience in Security & privacy chops (network allow‑lists and auditability)
- Fine‑tuning, KV‑cache strategies; code‑gen or test‑generation experience
- Experience integrating with developer tooling and doc systems
- 2+ years in applied ML/NLP or agentic systems; shipped LLM‑powered features to production
