Daice Labs
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 a Junior AI/ML Engineer in our R&D department. The Junior AI/ML Engineer will be responsible for developing and implementing AI and machine learning algorithms, conducting research on new AI methodologies, and applying statistical models to improve hybrid AI systems. Day-to-day tasks include analyzing data, building hybrid architectures (LLMs/DL, symbolic reasoning), and designing efficient evaluation benchmarks. Collaboration with cross-functional teams to integrate AI solutions into broader projects is also a key aspect of this role.
Qualifications
Strong foundation in Computer Science
Strong foundation in Machine learning algorithms, LLMs, agentic architectures
Proficiency in Statistics
Proficiency in python and ML stack programming languages/libraries/toolkits
Excellent problem-solving skills and ability to work independently
Effective communication skills for collaborative work
Bachelor’s or Master’s degree in Computer Science, AI, or related field
Experience with hybrid AI system design is a plus
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Join us in taking the next leap in productivity through collaborative innovation.
Role Description This is a full-time remote role for a Junior AI/ML Engineer in our R&D department. The Junior AI/ML Engineer will be responsible for developing and implementing AI and machine learning algorithms, conducting research on new AI methodologies, and applying statistical models to improve hybrid AI systems. Day-to-day tasks include analyzing data, building hybrid architectures (LLMs/DL, symbolic reasoning), and designing efficient evaluation benchmarks. Collaboration with cross-functional teams to integrate AI solutions into broader projects is also a key aspect of this role.
Qualifications
Strong foundation in Computer Science
Strong foundation in Machine learning algorithms, LLMs, agentic architectures
Proficiency in Statistics
Proficiency in python and ML stack programming languages/libraries/toolkits
Excellent problem-solving skills and ability to work independently
Effective communication skills for collaborative work
Bachelor’s or Master’s degree in Computer Science, AI, or related field
Experience with hybrid AI system design is a plus
#J-18808-Ljbffr