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Temporary Embedded Machine Learning Jobs (NOW HIRING)

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Qualcomm

Machine Learning Compiler

New York, NY · On-site

$140K - $211K/yr

As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques ... of experience in embedded system development and optimization with application to a specific ...

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Nutanix

Machine Learning Compiler

Manhattan, NY · On-site

$141 - $211/hr

... of experience in embedded system development and optimization with application to a specific ... Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model ...

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration. * Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems. At MatrixSpace, Machine Learning ...

PassFort

Machine Learning Engineer

Berlin, MD · On-site

$79.93 - $137.02/hr

Practical experience deploying deep learning models in real time on embedded hardware (TensorRT, ONNX, Jetson/Orin). * Solid understanding of machine learning, deep learning, and autonomous systems.

sensmore

Machine Learning Engineer

Berlin, NH · On-site

$102.41 - $159.31/hr

Practical experience deploying deep learning models in real time on embedded hardware (TensorRT, ONNX, Jetson/Orin). * Solid understanding of machine learning, deep learning, and autonomous systems.

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM ... Experience in a customer-facing or embedded delivery role. * Exposure to federated or privacy ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

They are seeking a Director of Machine Learning to define the ML strategy, lead the computer vision ... embedded inference) • Familiarity with warehouse, logistics, or supply chain domain • ...

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Temporary Embedded Machine Learning information

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$70K

$153.4K

$174K

How much do temporary embedded machine learning jobs pay per year?

As of Aug 23, 2026, the average yearly pay for temporary embedded machine learning in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Embedded Machine Learning vs Embedded Software Engineer?

AspectTemporary Embedded Machine LearningEmbedded Software Engineer
CredentialsRelevant degrees in CS, EE, or data science; certifications in ML or embedded systemsDegrees in CS, EE; certifications in embedded systems or software development
Work EnvironmentProject-based, often in tech or manufacturing industries, with focus on ML integrationDesigning, developing, and testing embedded software in various industries like automotive, IoT
Industry UsageUsed in AI-driven embedded systems, IoT devices, and smart gadgetsUsed in consumer electronics, automotive, industrial automation

Temporary Embedded Machine Learning specialists focus on integrating machine learning models into embedded devices, often on a project basis. Embedded Software Engineers develop and maintain the software that runs directly on hardware. While both roles require embedded systems knowledge, the ML role emphasizes AI integration, whereas the embedded software engineer focuses on software development and system stability.

What cities are hiring for Temporary Embedded Machine Learning jobs?

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What are the most commonly searched types of Embedded Machine Learning jobs?

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Temporary Embedded Machine Learning jobs near you

Machine Learning Engineer

Escalon Services, LLC.

Santa Monica, CA • On-site

$100K - $120K/yr

Full-time

Medical, PTO

Posted 17 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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