Daice Labs

About the Company

Daice Labs -- Digital co-builders engineering adaptation The Problem Current AI shines on benchmarks but breaks in the wild--brittle under distribution shift, costly to retrain, hard to audit, and slow to adapt. The need? new hybrid paradigms that integrate today's models into systems that learn continuously, generalize, and explain their decisions. Approach Founded by MIT CSAIL scientists, we build hybrid/composite frameworks that combine LLMs/DL with symbolic reasoning and bio-inspired system design to deliver new architectures. Our name Pronounced "dice." Dice evokes exploration; for us it's programmable adaptation. Two meanings. 1) DAICE = Data-driven AI for Context-aware Evolution. 2) Dais = or stage--an integrative platform for co-builders. Two focus tracks 1) Product Lab Building a collaboration platform where human teams co-build with hybrid AI. Features: shared context fabric, role-based models (ops, finance, R&D, commerce), vertical applications composed into a business-in-a-box, and co-ownership ledger audits for governance. 2) AI Research Lab Our lab investigates how principles of natural intelligence can guide the design of hybrid AI architectures. For example, living systems excel at "coordinated collaboration" via specialized structures or scaffolds. We believe that mimicking their system-level design will unlock new frameworks for AI generalization. - Translating biological, cellular, and evolutionary principles into system design. - Advancing perturbation-aware learning and rule-guided frameworks. - Developping cell-inspired architectures for guided program synthesis. The next Leap We believe that the next leap in productivity comes from collaboration--human teams and specialized AIs co-building on shared context, pushing boundaries for adaptation together. Interested? We're hiring-get in touch!

Listed Jobs

Company Name

Daice Labs

Job Title

AI/ML intern

Job Description

**Job Title** AI/ML Intern **Role Summary** Full‑time remote internship focused on researching and building hybrid AI systems that combine large language models, deep learning, symbolic reasoning, and bio‑inspired architectures. The intern will implement and test neural network and NLP models while collaborating on software solutions that support continuous learning and agentic behavior. **Expectations** - Contribute to the design and deployment of hybrid AI prototypes. - Deliver clean, well‑documented code and reproducible experiments. - Communicate progress and insights in cross‑functional meetings. - Demonstrate an ability to work independently while requesting timely feedback. **Key Responsibilities** - Implement, train, and evaluate pattern‑recognition, neural network, and NLP models (Python). - Develop APIs and JSON schemas for model and platform integration (TypeScript). - Build and maintain ML tooling, sandbox environments, and orchestration pipelines. - Manage containerized deployments, observability tooling, and data stores (PostgreSQL, Redis). - Construct evaluation pipelines: golden sets, regression testing, drift detection, and gating. - Apply security and privacy measures (network allow‑lists, audit trails). - Collaborate with product and research teams to iterate on hybrid AI prototypes. **Required Skills** - Strong foundation in pattern recognition, neural networks, and NLP. - Proficient in Python and TypeScript; comfortable with ML stacks and API design. - Experience with containerization (Docker/Kubernetes), observability, Postgres, Redis. - Prior work on ML platforms, agentic systems, or orchestration frameworks. - Knowledge of evaluation strategies: golden sets, regression, drift, gates. - Basic understanding of security/privacy controls for ML models. - Excellent problem‑solving, independent work, and communication skills. **Required Education & Certifications** - Currently enrolled or recently graduated with a degree in Computer Science, Engineering, or a related field (PhD status is a plus). - Relevant certifications (e.g., AWS Certified ML Specialty, TensorFlow Developer) are desirable but not mandatory.

Boston, United states

Remote

Fresher

09-11-2025