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Entry Level Machine Learning Engineer Jobs in Simi Valley, CA

Match Group

Machine Learning Engineer II

Los Angeles, CA · On-site

$105K - $143K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Match Group

Machine Learning Engineer II

Los Angeles, CA · On-site +1

$145K - $165K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Match Group

Machine Learning Engineer II

Los Angeles, CA · On-site +1

$105K - $143K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Escalon

Machine Learning Engineer

Santa Monica, CA

$100K - $120K/yr

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.

New

Capgroup

Senior Machine Learning Engineer

Los Angeles, CA

$132K - $174K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are looking for ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Simi Valley, CA

Entry Level Machine Learning Engineer information

See Simi Valley, CA salary details

$31K

$71.6K

$121.8K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for entry level machine learning engineer in Simi Valley, CA is $71,602.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,200.00 and $81,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What job categories do people searching Entry Level Machine Learning Engineer jobs in Simi Valley, CA look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Simi Valley, CA are:
What cities near Simi Valley, CA are hiring for Entry Level Machine Learning Engineer jobs? Cities near Simi Valley, CA with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Simi Valley, CA as of August 2026, with employment types broken down into 33% Internship, and 67% Full Time. Highlights an 33% In-person, 34% Hybrid, and 33% Remote job distribution, with an average salary of $71,602 per year, or $34.4 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