AI/ML Engineering Intern
daice labsSan Antonio (TX)
AI/ML Engineering Intern
Posted 12 days ago
daice labsSan Antonio (TX)
SENIORITY
Intern
About the role
Job Title: AI/ML Engineering Intern
Location: Brookline, MA (Remote within the United States)
Employment Type: Internship
About Daice LabsDaice 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 3-6 month internship (with potential for extension) to contribute to our research and engineering efforts remotely within the United States. 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 TensorFlowExperience with data preprocessing and dataset management
- Strong analytical and problem-solving skills
- Clear written and verbal communication skills
- Ability to work independently in a remote environment while meeting deadlines
- Must be authorized to work in the United States
- PreferredPrior experience contributing to AI/ML research projects or open-source repositories
- Familiarity with hybrid AI approaches, generative models, or symbolic AIExperience with version control (Git) and collaborative development workflows
- Coursework or projects in NLP, computer vision, or reinforcement learning
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, protected veteran status, or any other characteristic protected under national, state, or local law. Applicants with criminal histories will be considered in a manner consistent with applicable state and local laws. Daice Labs is a compliant corporation in MA with an e-verify account.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.