ZipRecruiter

Log In

1

Internship Machine Learning Robotics Jobs in California

Horizon Robotics

Research Scientist

Cupertino, CA · Hybrid

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

Waymo

Senior Machine Learning Engineer, Robotics

San Diego, CA · On-site

$110K - $152K/yr

Projects on our team typically require a diverse skill set, including robotics, system integration, code optimization, and machine learning. We have a good understanding of the hardware (both sensors ...

Machina Labs

Machine Learning Engineer

Los Angeles, CA

$160K - $190K/yr

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

This will require close collaboration with our robotics, research, and engineering team. Your work ... Deep understanding of state-of-the-art machine learning techniques and models. * Extensive industry ...

previous page

Showing results 41-60

All JobsMachine Learning Robotics JobsInternship Machine Learning Robotics JobsInternship Machine Learning Robotics Jobs in California

Internship Machine Learning Robotics information

What is the difference between Internship Machine Learning Robotics vs Internship Data Science?

AspectInternship Machine Learning RoboticsInternship Data Science
Required SkillsProgramming (Python, C++), Robotics, Machine LearningStatistics, Programming (Python, R), Data Analysis
Work EnvironmentRobotics labs, manufacturing, research facilitiesData centers, corporate offices, research institutions
Industry UsageRobotics companies, automation, AI hardwareFinance, healthcare, marketing, tech firms

Internship Machine Learning Robotics focuses on developing AI algorithms for robotic systems, combining hardware and software skills. In contrast, Internship Data Science emphasizes analyzing data to extract insights, often in business or research settings. Both internships require programming skills, but their applications and environments differ significantly.

How to become an internship machine learning robotics?

To become an intern in machine learning robotics, candidates typically need a background in computer science, robotics, or related fields, along with programming skills in languages like Python or C++. Gaining experience with machine learning frameworks such as TensorFlow or PyTorch and understanding robotics platforms like ROS can be beneficial. Applying to internships through university programs, online job portals, or company websites and demonstrating relevant coursework, projects, or certifications can improve chances of selection.

What are the most commonly searched types of Machine Learning Robotics jobs in California?

The most popular types of Machine Learning Robotics jobs in California are:

What cities in California are hiring for Internship Machine Learning Robotics jobs?

Cities in California with the most Internship Machine Learning Robotics job openings:

Internship Machine Learning Robotics jobs near you
Infographic showing various Internship Machine Learning Robotics job openings in California as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Machine Learning Engineer

Escalon Services, LLC.

Santa Monica, CA • On-site

$100K - $120K/yr

Full-time

Medical, PTO

Posted 18 days ago

Job description

Machine Learning Engineer
Application Deadline: 30 September 2026
Department: Recruiting Done
Employment Type: Full Time
Location: Santa Monica
Compensation: $100,000 - $120,000 / year
Description
About Our Client
Our client is a technology company developing next-generation intelligent systems at the intersection of AI, XR, robotics, autonomy, and spatial computing. Their products support mission-critical applications across defense, public safety, and critical infrastructure. They are seeking passionate professionals who thrive in fast-paced environments and enjoy building impactful products from concept to deployment.
The Role
Our client is seeking a Machine Learning Engineer to help design and implement intelligent systems that extract meaning and predictive value from computer vision and behavioral datasets. This is a junior-level, in-person role suited for candidates with 2-3 years of experience and a solid foundation in deep learning, embeddings, and modern neural architectures.
As a member of the AI team, the ideal candidate will work on projects that leverage CNNs, transformer models, and embedding architectures to encode and reason over pose, facial, and action-based visual data. These systems support downstream tasks such as future action prediction, semantic matching, and similarity-based inference.
Key Responsibilities
  • Design and implement machine learning pipelines that encode visual input (pose, face, object/classification) into shared embedding spaces for similarity and predictive tasks.
  • Build and fine-tune convolutional and transformer-based neural architectures optimized for visual recognition and representation learning.
  • Develop encoding and embedding techniques that allow consistent comparison across multiple data types (e.g., pose vectors, facial landmarks, class labels).
  • Apply techniques such as cosine similarity, distance metrics, and latent clustering to perform behavioural inference and action prediction.
  • Contribute to model training, evaluation, and deployment workflows, including data preprocessing, augmentation, hyperparameter tuning, and performance profiling.
  • Collaborate closely with engineers in computer vision, embedded systems, software, and UI/UX to ensure seamless integration of AI pipelines into real-time systems.
  • Produce clean, well-documented code and maintain version-controlled model artefacts and experiment logs.
  • Write technical documentation for models, training procedures, evaluation criteria, and system integration.

Skills, Knowledge and Expertise
  • Bachelor's or Master's degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or a closely related discipline.
  • 2-3 years of experience in machine learning roles through internships, academic labs, or early career positions.
  • Strong understanding of Convolutional Neural Networks (CNNs) for image and video-based tasks.
  • Strong understanding of transformer architectures and their applications in vision or multimodal learning.
  • Strong understanding of embedding systems and vector space modeling for semantic and similarity-based tasks.
  • Strong understanding of encoding mechanisms and dimensionality reduction techniques for latent representation.
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Familiarity with pose estimation, facial recognition, or classification models (e.g., OpenPose, MediaPipe, FaceNet, ResNet variants).
  • Experience training models with structured and unstructured visual datasets.
  • Exposure to techniques like cosine similarity, triplet loss, contrastive learning, or temporal prediction modeling.
  • Strong computer science fundamentals, including data structures, algorithms, and software design patterns.
  • Comfort working in Linux-based development environments and version control systems (Git).
  • A collaborative mindset, with excellent communication skills and a willingness to learn across domains.

Bonus (Nice to have):
  • Experience integrating vision-based AI models into embedded or robotics systems.
  • Familiarity with ONNX or TensorRT for model optimization and deployment.
  • Background in sequence modeling, recurrent architectures, or video-based action recognition.
  • Exposure to multimodal AI systems that blend image, pose, and metadata representations.
  • Familiarity with techniques like CLIP, DINO, or self-supervised representation learning.
  • Experience with MLOps or training orchestration tools such as MLflow, Weights & Biases, or DVC.

Other Requirements:
  • Must be a US Citizen or a valid Green Card holder. Visa sponsorship is not available for this role at this time.
  • Candidates must reside within a commutable distance of Santa Monica, California.

Benefits
  • Compensation: $100,000 to $120,000 per year
  • Comprehensive health coverage and flexible PTO
  • Opportunity to work on innovative AI, robotics, XR, and autonomous technologies
  • Collaborative multidisciplinary engineering environment
  • Career growth and professional development opportunities

Apply