AI/ML Engineering Intern
Location
Remote, India
Work type
Remote
Employment
Internship
Experience
0-1 years
Compensation
Compensation not disclosed
Posted
6d ago
Summary and responsibilities
Role overview
Summary
The AI/ML Engineering Intern will support the design and implementation of machine learning models, conduct experiments, and assist in building data pipelines. This role involves contributing to codebase improvements, testing, and documentation while participating in team meetings and code reviews.
About Daice Labs
Daice Labs, founded by MIT CSAIL scientists, is at the forefront of developing hybrid AI infrastructure designed for long-term, complex tasks. Our technology combines advanced AI models with neurosymbolic methods and bio-inspired system design to enable improved adaptability, verification, and context retention. We prioritize collaboration by empowering human teams to co-build and co-own outcomes while providing tools for governance, persistent context, and domain-specific environments. Our innovative approach fosters adaptive learning, creating reusable building blocks for solutions across varied domains. Join us in shaping the future of governed, continuous-learning AI systems.
About the Role
We are hiring an AI/ML Engineering Intern for a 3-month internship (with potential for extension) to contribute to our research and engineering efforts remotely from India. You will work directly with senior engineers and researchers on active projects, gaining hands-on experience with production ML systems and hybrid AI architectures.
Responsibilities
Support the design and implementation of machine learning models under the guidance of senior engineers
Conduct experiments, analyze results, and document findings
Assist in building and maintaining data pipelines and preprocessing workflows
Contribute to codebase improvements, testing, and documentation
Participate in team meetings, code reviews, and technical discussions
Qualifications
Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field
Foundational knowledge of machine learning concepts, statistical modeling, and data structures
Proficiency in Python and familiarity with ML libraries such as PyTorch or TensorFlow
Experience with data preprocessing and dataset management
Strong analytical and problem-solving skills
Clear written and verbal communication skills in English
Ability to work independently in a remote environment while meeting deadlines
Preferred
Prior experience contributing to AI/ML research projects or open-source repositories
Familiarity with hybrid AI approaches, generative models, or symbolic AI
Experience with version control (Git) and collaborative development workflows
Compensation: This is a paid internship. Details will be discussed during the interview process.
Duration: 3-6 months, with the possibility of extension based on mutual fit and project needs.
Equal Opportunity
Daice Labs is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, national origin, disability, or any other characteristic protected under applicable law.
Updated 6d ago
Candidate fit
Skills and qualifications
Additional skills
Experience
0-1 years
How this role is positioned
Role classification
Job domains
Industries
Employment
Internship
Contract duration
Permanent
Hiring type
Direct
Global hiring
Location specific
Offer details
Compensation and benefits
Compensation
Compensation not disclosed
Location, schedule, and role shape
Work setup
Work conditions
Bandwidth profile
Context on the employer
Company snapshot
Company
Daice Labs
Team size
Growing team
Location
Remote, India
Daice Labs, founded by MIT CSAIL scientists, is at the forefront of developing hybrid AI infrastructure designed for long-term, complex tasks. Our technology combines advanced AI models with neurosymbolic methods and bio-inspired system design to enable improved adaptability, verification, and context retention. We prioritize collaboration by empowering human teams to co-build and co-own outcomes while providing tools for governance, persistent context, and domain-specific environments. Our innovative approach fosters adaptive learning, creating reusable building blocks for solutions across varied domains. Join us in shaping the future of governed, continuous-learning AI systems.
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AI/ML Engineering Intern
Remote, India • Internship