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Freelance Full Stack Machine Learning Engineer Jobs in California

XPENG

Staff Machine Learning Engineer

Santa Clara, CA · On-site

Debug issues across the full stack, including data quality, labeling, model behavior, evaluation ... Electrical Engineering, Robotics, Computer Vision, Machine Learning, or a related field. * 3-5 ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

They are seeking a Machine Learning Engineer to translate research into scalable solutions ... processing stacks such as Spark and Airflow. • Experience with multi-node GPU training. • ...

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

In this role, you will work across the full ML lifecycle -- from data preparation and feature ... Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

You'll work across the full machine learning lifecycle, from experimentation and model and agent ... Learning Engineer, or related role * Prior experience at a frontier AI lab, agentic startup ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... the machine learning stack, and who move fast and take ownership of their projects. Our ideal ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... the machine learning stack, and who move fast and take ownership of their projects. Our ideal ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

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All JobsFull Stack Machine Learning Engineer JobsFreelance Full Stack Machine Learning Engineer JobsFreelance Full Stack Machine Learning Engineer Jobs in California

Freelance Full Stack Machine Learning Engineer information

What is the difference between Freelance Full Stack Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Full Stack Machine Learning EngineerFreelance Data Scientist
CredentialsProficiency in programming, machine learning, and full stack developmentStrong statistical, analytical, and programming skills, often with data analysis certifications
Work EnvironmentDevelops and deploys ML models, works on both front-end and back-end systemsAnalyzes data, builds models, and provides insights, mainly focusing on data analysis
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, reporting, and predictive modeling

Freelance Full Stack Machine Learning Engineers focus on building and deploying machine learning models within full stack applications, combining software development with ML expertise. Freelance Data Scientists primarily analyze data and create models for insights. While both roles require programming skills, the engineer's role emphasizes deployment and integration, whereas the data scientist's role centers on analysis and interpretation.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in California?

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For Freelance Full Stack Machine Learning Engineer jobs in California, the most frequently searched job titles are:

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Freelance Full Stack Machine Learning Engineer jobs near you

Staff Machine Learning Engineer

XPENG

Santa Clara, CA • On-site

Full-time

Re-posted 14 days ago

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
About the Role
We are looking for a strong Machine Learning Engineer / Computer Vision Engineer to work on Traffic Sign Recognition (TSR) 2D detection for production autonomous driving systems.
In this role, you will be responsible for the full lifecycle of TSR model development, including scenario analysis, data preparation, model training, evaluation, optimization, quantization, and deployment. You will work closely with perception, data, infrastructure, and deployment teams to improve traffic sign detection performance across diverse real-world driving scenarios.
This role is ideal for candidates who enjoy solving practical computer vision problems, building reliable model iteration pipelines, and bringing perception models from offline training to onboard production systems.
Job Responsibilities
  • Develop and improve traffic sign detection models for autonomous driving perception systems.
  • Investigate and Experiment DETR/Transformer-based TSR models for accurate and stable/robust traffic sign detection across diverse driving scenarios.
  • Analyze TSR-related scenarios and failure cases, including missed detections, false positives, occlusions, small objects, rare signs, region-specific signs, and adverse weather or lighting conditions.
  • Improve VLA models to effectively consume TSR outputs and support traffic-sign-aware instruction following through VLA prompts.
  • Prepare, clean, curate, and analyze training and evaluation datasets for TSR model iteration.
  • Design and execute model training experiments, including data sampling, augmentation, loss tuning, class imbalance handling, and hard-case mining.
  • Build and maintain evaluation pipelines for TSR models, including offline metrics, scenario-based evaluation, regression testing, and error analysis.
  • Collaborate with data teams to define mining strategies for long-tail TSR scenarios and improve dataset coverage.
  • Optimize models for production deployment, including ONNX / TensorRT / quantization / inference acceleration.
  • Work with deployment and platform teams to validate model performance on onboard or edge compute platforms.
  • Track model performance across versions and support continuous improvement through data-model-evaluation feedback loops.
  • Debug issues across the full stack, including data quality, labeling, model behavior, evaluation mismatch, and deployment consistency.

Basic Qualifications
  • Master's, or PhD degree in Computer Science, Electrical Engineering, Robotics, Computer Vision, Machine Learning, or a related field.
  • 3-5 years of strong hands-on experience with computer vision models, especially object detection.
  • Experience with detection architectures such as YOLO, Faster R-CNN, DETR/Deformable DETR, RT-DETR, RTMDet, or similar models.
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Solid understanding of object detection training workflows, including dataset preparation, augmentation, loss functions, evaluation metrics, and model debugging.
  • Experience with common detection metrics such as mAP, precision/recall, false positive/false negative analysis, and class-level performance breakdown.
  • Strong data analysis and problem-solving skills.
  • Ability to work cross-functionally with model, data, infrastructure, and deployment teams.

Preferred Qualifications
  • Experience in autonomous driving, ADAS, robotics, or safety-critical perception systems.
  • Experience with traffic sign recognition, traffic light recognition, road object detection, or small-object detection.
  • Familiarity with long-tail scenario mining, hard negative mining, class imbalance handling, and dataset curation.
  • Experience with ONNX, TensorRT, model quantization, C++ inference pipelines, CUDA, or edge deployment.
  • Experience debugging training-to-deployment consistency issues, including preprocessing mismatch, postprocessing mismatch, quantization accuracy drop, or runtime performance bottlenecks.
  • Familiarity with large-scale data pipelines, scenario tagging, or automated data mining workflows.
  • Strong engineering discipline in experiment tracking, reproducibility, regression testing, and model version management.
What Success Looks Like
A successful engineer in this role will:
  • Improve TSR detection performance across both common and long-tail traffic sign scenarios.
  • Build reliable data and evaluation workflows to support fast model iteration.
  • Identify and prioritize high-impact failure modes through scenario analysis and data mining.
  • Deliver deployable TSR models with strong accuracy, latency, and robust tradeoffs.
  • Help establish a scalable data-model-evaluation-deployment loop for production TSR development.
Why Join Us
  • Work on production of autonomous driving perception systems with real-world impact.
  • Own an important perception task that directly affects driving safety, rule understanding, and product quality.
  • Collaborate with strong teams across model development, data, deployment, and vehicle platforms.
  • Gain hands-on experience across the full model lifecycle: from data and training to evaluation, optimization, quantization, and onboard deployment.

What do we provide
  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • Opportunity to make a significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Competitive compensation package.
  • Snacks, lunches, dinners, and fun activities.

The base salary range for this full-time position is $179,400 - $303,600, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

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