Data & AnalyticsHybrid

Intern - Software/ML Engineer

Human Computer Lab · Hybrid

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Last seen by MeritLog September 9, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Human Computer Lab's Ashby job board and last checked it on September 9, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: Hybrid
Salary: Not listed by source
Location: San Francisco

Hiring context

How this role compares at Human Computer Lab

Human Computer Lab has 14 live roles in MeritLog’s catalog across 4 job families, and 2 of them are in data & analytics. 0 of those listings publish a pay range, a disclosure rate of 0%.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

Develop software systems for robotic platforms that power robot perception, intelligence, and behavior
Build machine learning models for tasks such as computer vision, audio processing, and interaction understanding
Design and implement pipelines for training and deploying machine learning models
Integrate ML systems with robotic hardware and embedded systems
Improve robot perception, responsiveness, and behavioral intelligence
Collaborate with robotics engineers to build integrated robotic systems
Are passionate about building intelligent physical systems.
Move quickly and work well in rapid iteration cycles.
Take ownership over the systems they design and build.
Are curious, resourceful, and motivated to solve difficult problems.
Work well in small, collaborative teams.
Consider not just what immediately works, but how consumers will engage with robots.

What they're asking for

Are pursuing a degree in Computer Science, Electrical Engineering, Computer Engineering, or a related fieldEducation
Have strong programming skills in Python and/or C++ as well as an understanding of algorithms and software engineering fundamentals.Skill
Have experience with machine learning frameworksSkill
Have experience in one or more of the following areas: computer vision, robotics, reinforcement learning, or multimodal AISkill
Have experience building and deploying machine learning systems preferably in Simulations (Issac Sim, MJLab, Mujoco, etc.)Skill
Are comfortable jumping into unfamiliar systems and can create order through chaos.Skill
Care about users and feel ownership over outcomes, even for systems you don't own.Skill
Think holistically about systems and approach complex problems with creative, outside-the-box solutions.Skill

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

Human Computer Lab is a research lab building character robots that feel alive and responsive. Our first robot, LeLamp, explores a new category of consumer robotics where everyday objects become interactive and help us reshape our attachment to technology. Our goal is to push the frontier of human-robot interaction by making technology more legible, emotionally intuitive, and human-centered. We are building the foundation for a new generation of robots designed for everyday environments. What to expect As an intern, you will be responsible for helping build the software and machine learning systems that power robot perception, intelligence, and behavior. You will work closely with the team to develop and deploy ML models, build real-time software systems, and integrate machine learning with robotic hardware - turning research and simulation into reliable, production-ready robotics software. In this role, you will: - Develop software systems for robotic platforms that power robot perception, intelligence, and behavior - Build machine learning models for tasks such as computer vision, audio processing, and interaction understanding - Design and implement pipelines for training and deploying machine learning models - Integrate ML systems with robotic hardware and embedded systems - Improve robot perception, responsiveness, and behavioral intelligence - Collaborate with robotics engineers to build integrated robotic systems You may be a good fit if you: - Are pursuing a degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field - Have strong programming skills in Python and/or C++ as well as an understanding of algorithms and software engineering fundamentals. - Have experience with machine learning frameworks - Have experience in one or more of the following areas: computer vision, robotics, reinforcement learning, or multimodal AI - Have experience building and deploying machine learning systems preferably in Simulations (Issac Sim, MJLab, Mujoco, etc.) - Are comfortable jumping into unfamiliar systems and can create order through chaos. - Care about users and feel ownership over outcomes, even for systems you don't own. - Think holistically about systems and approach complex problems with creative, outside-the-box solutions. You will be a strong fit, if you: - Are passionate about building intelligent physical systems. - Move quickly and work well in rapid iteration cycles. - Take ownership over the systems they design and build. - Are curious, resourceful, and motivated to solve difficult problems. - Work well in small, collaborative teams. - Consider not just what immediately works, but how consumers will engage with robots. The early team becomes the DNA of the company. We set ourselves and others to a high standard, and we respond with kindness when things get hard but keep everyone accountable. This requires us to be curious, creative, and diverse in our thinking and approach. We’re proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Even if you don’t meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don’t want that to be the reason we miss out on great talent.

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