1

Quantum Machine Learning Engineer Jobs in Santa Clara, CA

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 ...

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 ...

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 ...

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

Machine Learning Engineer

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Position starts off as a 6 month contract Machine Learning Engineer Location: Pleasanton, California (Remote) Role Overview This role is focused on developing, deploying, and optimizing machine ...

next page

Showing results 1-20

Quantum Machine Learning Engineer information

See Santa Clara, CA salary details

$37K

$151.2K

$227.3K

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

As of Aug 23, 2026, the average yearly pay for quantum machine learning engineer in Santa Clara, CA is $151,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $182,000.00 per year, depending on experience, location, and employer.

What is a quantum machine learning engineer?

A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.

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

To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.

How do quantum machine learning engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, focusing on developing algorithms that leverage quantum hardware. The field is emerging with high growth potential, requiring skills in quantum algorithms, programming languages like Python, and understanding of both quantum mechanics and machine learning principles. As quantum technology advances, demand for specialists in this area is expected to increase, making it a promising career path for those with relevant expertise.

What are popular job titles related to Quantum Machine Learning Engineer jobs in Santa Clara, CA?

For Quantum Machine Learning Engineer jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Quantum Machine Learning Engineer jobs in Santa Clara, CA look for?

The top searched job categories for Quantum Machine Learning Engineer jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Quantum Machine Learning Engineer jobs?

Cities near Santa Clara, CA with the most Quantum Machine Learning Engineer job openings:

Machine Learning Engineer

Advatix Inc.

San Mateo, CA • On-site

$110 - $165/hr

Other

Medical, Dental, Vision, PTO

Posted 17 days ago


Job description

Department: Information Technology, Type: Full Time

Job Title: 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 Sponsorship: Not Available

Relocation Assistance: Not Available

Role Summary

We are looking for a highly skilled Machine Learning Engineer / Research Engineer to join our founding team and help develop intelligent systems that transform how hardware and mechanical engineers design products. This is a unique opportunity to work at the intersection of cutting‑edge machine learning research and real‑world engineering applications. You'll collaborate directly with founders, engineers, and customers to design, train, deploy, and continuously improve machine learning systems that accelerate CAD workflows and hardware design. As one of the earliest ML hires, you will have significant ownership over technical direction, architecture decisions, and the long‑term evolution of our AI platform.

Key Responsibilities Machine Learning Research & Development
  • Design, train, and optimize custom deep learning models that understand CAD workflows and generate intelligent next‑step design recommendations.
  • Develop novel machine learning approaches for geometry, design, and engineering‑related datasets.
  • Evaluate emerging research in areas such as sequence modeling, geometric deep learning, representation learning, and foundation models.
Data & Model Infrastructure
  • Build and maintain scalable Python‑based training, evaluation, and experimentation pipelines.
  • Transform complex, real‑world CAD and geometry data into high‑quality training datasets and signals.
  • Implement robust offline and online evaluation frameworks to measure model performance and business impact.
Production ML Systems
  • Own the complete ML lifecycle from research and prototyping through deployment, monitoring, and optimization.
  • Architect model‑serving infrastructure and backend components that enable fast, reliable integration into CAD environments.
  • Establish best practices for experimentation, logging, model versioning, and performance monitoring.
Cross‑Functional Collaboration
  • Work closely with founders, mechanical engineers, hardware engineers, and early customers to understand workflows and translate them into ML solutions.
  • Collaborate with backend engineers on APIs, infrastructure, data models, and platform scalability.
  • Help define the long‑term strategy for applying machine learning to hardware and CAD design.
Skills & Qualifications Machine Learning Expertise
  • 4+ years of hands‑on machine learning experience in industry, research, or a combination of both.
  • Equivalent Master's or PhD research experience will be considered.
  • Demonstrated success designing, training, improving, and deploying machine learning models—not simply utilizing hosted AI APIs.
Deep Learning & Research
  • Expert‑level proficiency with PyTorch (preferred) or similar frameworks such as TensorFlow or JAX.
  • Experience implementing custom architectures, loss functions, optimization methods, and training loops.
  • Strong understanding of model evaluation, experimentation, and performance trade‑offs.
Software Engineering
  • Strong Python programming skills with experience building production‑ready systems.
  • Ability to write clean, maintainable, and well‑tested code with appropriate documentation and abstractions.
  • Experience developing scalable ML infrastructure and backend services.
Ownership & Execution
  • Proven ability to independently drive projects from concept through deployment.
  • Experience building end‑to‑end ML systems including data pipelines, experimentation frameworks, model training, deployment, and monitoring.
  • Comfortable solving ambiguous, open‑ended technical problems.
Communication & Collaboration
  • Excellent communication skills with the ability to explain technical concepts to both technical and non‑technical stakeholders.
  • Experience working cross‑functionally with engineers, product teams, researchers, and customers.
Startup Mindset
  • Thrives in fast‑paced, high‑ownership environments.
  • Comfortable wearing multiple hats across machine learning, research, backend engineering, and infrastructure.
Preferred Qualifications
  • Published research papers or meaningful open‑source contributions demonstrating novel technical work.
  • Experience with:
    • CAD systems and workflows
    • Computational geometry
    • Computer graphics
    • 3D representations
    • Robotics
    • Familiarity with cloud ML infrastructure (AWS, GCP).
    • Experience with backend frameworks such as FastAPI, Flask, or Django.
Must‑Have Requirements
  • Must be based in the United States and possess valid work authorization.
  • Strong proficiency in Python and modern deep learning frameworks (PyTorch preferred).
  • Demonstrated experience building and deploying custom machine learning models from scratch.
  • Experience designing architectures, creating training pipelines, and shipping ML features to production.
  • Minimum 4 years of relevant industry or equivalent academic experience.
Benefits & Perks
  • Competitive salary ($110,000 – $175,000)
  • Meaningful equity ownership
  • Comprehensive medical, dental, and vision insurance
  • Catered team lunches at the San Mateo office
  • Unlimited/flexible paid time off
  • High‑impact role within a YC‑backed startup
  • Direct collaboration with experienced founders and engineers
  • Significant opportunities for growth, learning, and career advancement
  • Opportunity to help define the future of AI‑powered CAD and hardware design

HRforGrowthis an extension of the Growth Catalyst Group (GCG), a partnership of companies with more than 65 years of operating experience and a history of successfully serving customers across industries and disciplines.

GCG® is one of the world’s leading providers of business transformation solutions related to supply chain and technology solutions for order fulfillment and marketing execution. We are committed to an inclusive workplace that does not discriminate against race, nationality, religion, age, marital status, physical or mental disability, sexual orientation, gender, orgender identity. We believe in diversity and encourage anyqualifiedindividual to apply. We are an EEOCEmployer.

#J-18808-Ljbffr