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Machine Learning Software Engineer Jobs in Los Angeles, CA

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for building reliable, scalable machine learning systems. Responsibilities * Support the deployment ...

Motorola

Machine Learning Engineer

Los Angeles, CA

$150K - $180K/yr

Manage inputs gathered from unusual sources, including captures from software defined radio (SDR ... Bachelor degree with 4+ years experience as a machine learning engineer * AND 2+ years of Python ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA

$140K - $170K/yr

The Sr Engineer, AI & ML will also closely work with our software, hardware and systems teams to ... Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ...

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All JobsMachine Learning Software Engineer JobsMachine Learning Software Engineer Jobs in Los Angeles, CA

Machine Learning Software Engineer information

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$68.4K

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How much do machine learning software engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning software engineer in Los Angeles, CA is $158,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,300.00 and $186,400.00 per year, depending on experience, location, and employer.

Is machine learning software engineer a high paying job?

Machine learning software engineers typically earn high salaries due to the specialized skills required, such as proficiency in programming languages like Python and experience with frameworks like TensorFlow. Salaries vary based on experience, location, and industry, but generally rank above average compared to other software engineering roles.

What does a machine learning software engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

What are the key skills and qualifications needed to thrive as a machine learning software engineer?

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the most commonly searched types of Machine Learning Software Engineer jobs in Los Angeles, CA? The most popular types of Machine Learning Software Engineer jobs in Los Angeles, CA are:
What are popular job titles related to Machine Learning Software Engineer jobs in Los Angeles, CA? For Machine Learning Software Engineer jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Software Engineer jobs in Los Angeles, CA look for? The top searched job categories for Machine Learning Software Engineer jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Machine Learning Software Engineer jobs? Cities near Los Angeles, CA with the most Machine Learning Software Engineer job openings:
Machine Learning Software Engineer jobs near you
Infographic showing various Machine Learning Software Engineer job openings in Los Angeles, CA as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $158,958 per year, or $76.4 per hour.

Machine Learning Engineer

Escalon Services, LLC.

Santa Monica, CA • On-site

$100K - $120K/yr

Full-time

Medical, PTO

Posted 3 days ago

New

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