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Internship Computer Vision Robotics Jobs in New York

Mecka AI

Human Data Architect, Quality

New York, NY · On-site

$130K - $160K/yr

Background in computer vision, robotics, cognitive science, linguistics, or a related field where taxonomy design is craft. * Have strong opinions about data quality you can defend with concrete ...

New York University

Post Doctoral Associate

New York, NY · On-site

$62K - $80K/yr

Description Post Doctoral Associate NYU Tandon School of Engineering Post-Doctoral Positions in Robotics, Controls, AI, Computer Vision, and Hardware Security The Control/Robotics Research Laboratory ...

Radical AI

Perception Engineer

New York, NY

$175K - $225K/yr

Degree in Robotics, Computer Vision, Electrical Engineering, Computer Science, or a related field * 5+ years of experience designing and deploying machine vision systems in robotics or automation ...

Radical AI

Perception Engineer

New York, NY · On-site

$175K - $225K/yr

Degree in Robotics, Computer Vision, Electrical Engineering, Computer Science, or a related field * 5+ years of experience designing and deploying machine vision systems in robotics or automation ...

Hayden AI

Staff Software Engineer

New York, NY · On-site

$230K - $299K/yr

This role requires deep expertise in computer vision and/or robotics algorithms that are deployed on the edge/cloud. You will be responsible for setting the technical direction and standards for the ...

Hayden AI

Senior Software Engineer

New York, NY · On-site

$200K - $260K/yr

Substantial background in a minimum of one of the following domains: robotics, state estimation, computer vision, or applied machine learning. * Senior-level industrial experience in the delivery of ...

Radical AI

Perception Engineer

New York, NY

$175K - $225K/yr

Degree in Robotics, Computer Vision, Electrical Engineering, Computer Science, or a related field * 5+ years of experience designing and deploying machine vision systems in robotics or automation ...

Mini-Circuits

Automation Systems Engineer II

New York, NY · On-site

$100K - $125K/yr

Experience with robotic systems, automated handlers, or precision motion/vision-based automation. * Familiarity with high-mix/low-to-medium volume manufacturing environments. * CAD proficiency ...

silana

Field Service Engineer - Robotics

New York, NY

$75K - $85K/yr

Our machines integrate robotic manipulation, computer vision, AI, industrial controls, and embedded compute to automate sewing and assembly operations that are still performed manually in most of the ...

Silana

Field Service Engineer - Robotics

New York, NY · On-site

$75K - $85K/yr

Our machines integrate robotic manipulation, computer vision, AI, industrial controls, and embedded compute to automate sewing and assembly operations that are still performed manually in most of the ...

silana

Field Service Engineer - Robotics

New York, NY · On-site

$75K - $85K/yr

Our machines integrate robotic manipulation, computer vision, AI, industrial controls, and embedded compute to automate sewing and assembly operations that are still performed manually in most of the ...

Mini-Circuits

Automation Systems Engineer II

New York, NY · On-site

$100K - $125K/yr

Experience with robotic systems, automated handlers, or precision motion/vision-based automation. * Familiarity with high-mix/low-to-medium volume manufacturing environments. * CAD proficiency ...

Norbert Health

Applied AI Engineer

Brooklyn, NY · On-site

Job Summary : Norbert Health is building autonomous robots that deliver healthcare. They are ... processing, computer vision) on integration with their lower-level pipelines Qualifications

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Internship Computer Vision Robotics information

What are the key skills and qualifications needed to thrive as an internship computer vision robotics?

To thrive in an Internship Computer Vision Robotics role, you typically need a solid background in computer science, mathematics, and robotics, often supported by coursework or projects in machine learning and image processing. Familiarity with programming languages like Python or C++, and experience using tools such as OpenCV, ROS, and deep learning frameworks (e.g., TensorFlow or PyTorch) are commonly required. Strong problem-solving, teamwork, and effective communication skills set candidates apart in multidisciplinary environments. These skills are essential for developing innovative solutions and collaborating on complex robotics projects.

What types of projects and technologies will I typically work on during an internship in computer vision robotics?

As an intern in computer vision robotics, you will often work on hands-on projects involving tasks like object detection, image segmentation, sensor data processing, or robotic navigation. You may use programming languages like Python or C++, and frameworks such as OpenCV, ROS (Robot Operating System), and TensorFlow or PyTorch for machine learning components. Interns collaborate closely with engineers and researchers, participating in code reviews, testing algorithms on real or simulated robots, and troubleshooting system integration. This role offers exposure to both software development and hardware interaction, providing a comprehensive experience in robotics and computer vision.

What is an internship computer vision robotics?

Internship Computer Vision Robotics positions are temporary roles designed for students or early-career professionals to gain practical experience in applying computer vision techniques within robotic systems. Interns in these roles typically work on projects involving image processing, object detection, 3D vision, and integrating visual data into robotic control systems. These internships help candidates build technical skills, gain exposure to real-world robotics challenges, and often require knowledge of programming languages such as Python or C++, as well as familiarity with machine learning frameworks. They are commonly offered by research labs, tech companies, and robotics startups.

What is the difference between Internship Computer Vision Robotics vs Internship Machine Learning?

AspectInternship Computer Vision RoboticsInternship Machine Learning
Required CredentialsRelevant coursework, basic programming skills, familiarity with robotics and vision toolsProgramming skills, math background, familiarity with algorithms and data analysis
Work EnvironmentRobotics labs, hardware integration, software developmentData analysis, software development, research environments
Employer & Industry UsageRobotics companies, research labs, tech firms working on autonomous systemsTech companies, research institutions, AI startups

Internship Computer Vision Robotics focuses on developing systems that enable robots to interpret visual data, combining hardware and software skills. In contrast, Internship Machine Learning emphasizes designing algorithms to analyze data and build predictive models. Both roles require programming knowledge but differ in their application areas and work environments.

What are popular job titles related to Internship Computer Vision Robotics jobs in New York? For Internship Computer Vision Robotics jobs in New York, the most frequently searched job titles are:
What job categories do people searching Internship Computer Vision Robotics jobs in New York look for? The top searched job categories for Internship Computer Vision Robotics jobs in New York are:
What cities in New York are hiring for Internship Computer Vision Robotics jobs? Cities in New York with the most Internship Computer Vision Robotics job openings:
Internship Computer Vision Robotics jobs near you
Infographic showing various Internship Computer Vision Robotics job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Human Data Architect, Quality

Mecka AI

New York, NY • On-site

$130K - $160K/yr

Full-time

Re-posted 8 days ago

Job description

About Mecka AI
Mecka AI is building the data and deployment infrastructure for embodied intelligence. We collect, curate, and license the world's most useful robotics training data to leading AI labs, and we deploy real robotic systems with enterprise customers across hospitality, retail, QSR, pharmacy, logistics, and healthcare. We work with the foundation model teams shaping the next decade of robotics, and with the operators running real businesses today. Quality, trust, and execution are core to our partnerships.
The Role
We're hiring a Human Data Architect, Quality to be the person with taste for what robotics training data should look like at Mecka. You will define what good data is - the labeling rubrics, ontologies, schemas, sampling philosophy, and acceptance criteria that every dataset we ship is measured against. You decide what goes in or out of a dataset and why.
This is a standards-and-methodology architecture role, not a QA-management role. You set the quality bar; data operations and QA teams enforce it. Your output is the spec the entire data org and our customers run on.
You will work shoulder-to-shoulder with foundation-model researchers at our customers to translate model behavior into data structure - what to label, how to label it, how to organize it, how to compose a training set, what the edge cases are, and what makes a dataset trainable versus merely large.
What You'll Own
Labeling Rubrics & Quality Criteria (per customer)
  • Define the labeling rubrics, severity levels, rejection taxonomies, and acceptance criteria for each customer program across video, sensor streams, trajectories, action labels, task outcomes, language grounding, and metadata.
  • Translate ambiguous customer requirements ("we want a model that can do X") into precise, measurable, executable data specifications.
  • Maintain customer-specific quality criteria and the canonical data dictionary every program references.
  • Build golden datasets, reference examples, and calibration tasks that define "correct" by demonstration, not just description.
Ontology & Data Organization
  • Own the taxonomy, schema, and class hierarchies for robotics datasets - how attributes are structured, how temporal segmentation works, how event boundaries are defined, how ambiguity is handled, how edge cases are categorized.
  • Decide how data is organized end-to-end so it is trainable, queryable, and composable across customers and modalities.
  • Set dataset versioning conventions, schema evolution rules, and the data-organization philosophy the org runs on.
Dataset Composition - What's In, What's Out
  • Own the philosophy for what goes into a dataset and what gets cut: distribution, diversity, edge-case representation, redundancy, license/provenance constraints.
  • Decide sampling strategies, balancing rules, and curation principles for each program.
  • Make taste-driven calls on what data is worth collecting at all - and push back when collection plans won't produce trainable data.
  • Define the acceptance bar that says "this dataset is ready to ship" - and hold it under deadline pressure.
Methodology Iteration from Model Signal
  • Iterate rubrics and ontology based on model-failure signal from customers - your standards evolve with what models actually struggle to learn.
  • Run cross-customer reviews of recurring quality misses and translate them into standards improvements.
  • Partner with engineering on automated validation (schema completeness, duplicates, time sync, metadata coverage, model-assisted review) so the standard is enforceable at scale.
Who You Are
Required Background
  • 5+ years working at the intersection of ML and data - annotation methodology, dataset curation, data-centric ML, ground truth design, or labeling-specifications work for autonomy, vision, or multimodal teams.
  • Hands-on experience designing taxonomies, ontologies, or labeling schemas that fed production model training (not just internal analytics).
  • Strong data instincts: you can open a dataset in SQL, a notebook, or Python and tell us what's wrong with it within an hour.
  • Comfortable reading ML papers and translating model-architecture needs into data-structure choices.
Strong Signals
  • Built a labeling rubric, ontology, or ground-truth spec that a large annotation org executed against in production.
  • Worked directly with research scientists at frontier AI labs or autonomy companies on what training data should contain.
  • Background in computer vision, robotics, cognitive science, linguistics, or a related field where taxonomy design is craft.
  • Have strong opinions about data quality you can defend with concrete examples.
You Are
  • A taste-maker. You believe data quality is a design problem, not a process problem.
  • Precise about definitions and obsessive about edge cases.
  • Confident saying "this dataset isn't useful and here's why" - to customers, to leadership, to research teams.
  • Energized by deciding the standard, not by managing the team that enforces it.
Why This Role
  • Define the data standards the foundation-model teams shaping the next decade of robotics will train on.
  • Be the person with the pen on what good robotics data looks like - across video, sensors, trajectories, and language.
  • Work directly with researchers at frontier AI labs, not through a sales or PM layer.
  • Build the methodology backbone of a data company at the moment the field is still deciding what "good" means.
What Success Looks Like
  • Every major customer program has a clear, documented quality standard, ontology, and acceptance criteria authored by you.
  • The data organization runs against a canonical schema and rubric set - not ad-hoc per-project decisions.
  • Customer rejection rates fall and dataset usefulness rises because the right data is being collected and labeled the right way the first time.
  • Researchers at customer labs treat you as the technical counterpart they want to talk to about what they're actually buying.
  • Standards evolve continuously from model-failure signal, not in annual rewrites.

Apply