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Entry Level Machine Learning Robotics Jobs in California

Skild AI

Research Scientist

San Mateo, CA · On-site

We are looking for people with proven expertise in machine learning and/or robotics, who are passionate about pushing the boundaries of what is possible. You will collaborate with a team of talented ...

Bosch Group

Research Scientist- Robotics AI

Sunnyvale, CA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

As a Research Scientist- Robotics AI, you contribute to research projects at the forefront of the ... Conduct research and engineering in core AI and machine learning fields to enable Embodied AI ...

Bosch Group

Research Scientist- Robotics AI

Sunnyvale, CA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

As a Research Scientist- Robotics AI, you contribute to research projects at the forefront of the ... Conduct research and engineering in core AI and machine learning fields to enable Embodied AI ...

Bosch Group

Research Scientist- Robotics AI

Sunnyvale, CA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

As a Research Scientist- Robotics AI, you contribute to research projects at the forefront of the ... Conduct research and engineering in core AI and machine learning fields to enable Embodied AI ...

Robert Bosch Group

Research Scientist- Robotics AI

Sunnyvale, CA · On-site

$165 - $185/hr

  • Medical

  • Life

  • Retirement

  • PTO

As a Research Scientist- Robotics AI, you contribute to research projects at the forefront of the ... Conduct research and engineering in core AI and machine learning fields to enable Embodied AI ...

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Entry Level Machine Learning Robotics information

What is the difference between Entry Level Machine Learning Robotics vs Entry Level Data Scientist?

AspectEntry Level Machine Learning RoboticsEntry Level Data Scientist
Required CredentialsBachelor's in CS, Robotics, or related; knowledge of ML, programmingBachelor's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRobotics labs, manufacturing, research facilitiesCorporate offices, research firms, tech companies
Industry UsageManufacturing, automation, robotics developmentFinance, healthcare, tech, marketing
Common Search/ComparisonYesYes

Entry Level Machine Learning Robotics focuses on developing and programming robotic systems using machine learning techniques, often in manufacturing or research settings. Entry Level Data Scientist emphasizes analyzing data to inform business decisions across various industries. While both roles require programming and analytical skills, their work environments and applications differ significantly.

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 are popular job titles related to Entry Level Machine Learning Robotics jobs in California?

For Entry Level Machine Learning Robotics jobs in California, the most frequently searched job titles are:

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Entry Level Machine Learning Robotics jobs near you
Infographic showing various Entry Level Machine Learning Robotics job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

Escalon Services, LLC.

Santa Monica, CA

$100K - $120K/yr

Full-time

Medical, PTO

Posted 13 days ago

Job 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.
  • 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.
  • 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.
  • 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

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