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Quantum Machine Learning Jobs in California (NOW HIRING)

A physics background is not required however, a keen desire to rapidly learn and upskill in quantum computing technologies is critical. * High performance computing and/or machine learning experience ...

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Quantum Machine Learning information

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$25.2K

$42K

$86.8K

How much do quantum machine learning jobs pay per year?

As of Aug 17, 2026, the average yearly pay for quantum machine learning in California is $42,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

What is a quantum machine learning?

A Quantum Machine Learning (QML) job involves applying principles of quantum computing to machine learning tasks. Professionals in this field develop algorithms that leverage quantum systems to improve computational efficiency and solve complex problems faster than classical methods. Responsibilities often include researching quantum algorithms, implementing quantum circuits, and working with tools like Qiskit or TensorFlow Quantum. These roles are typically found in research labs, tech companies, and startups exploring the intersection of AI and quantum technology. Strong backgrounds in quantum mechanics, linear algebra, and computer science are essential.

What does a quantum machine learning professional do?

Quantum Machine Learning professionals often work on exploratory projects at the intersection of quantum computing and artificial intelligence, such as developing new algorithms that leverage quantum hardware for faster data processing or optimizing classical ML models using quantum techniques. Daily tasks may include designing experiments, simulating quantum systems, analyzing results, and collaborating with physicists and software engineers. The work can range from foundational research to applied development, depending on the organization's focus. These roles frequently involve teamwork and staying updated on emerging academic and industry advances to ensure innovative problem-solving approaches.

What are the key skills and qualifications needed to thrive in quantum machine learning?

To thrive in Quantum Machine Learning, you need a solid background in quantum physics, machine learning, linear algebra, and programming—often supported by a graduate degree in a related field. Familiarity with quantum computing frameworks such as Qiskit or Cirq, and experience with conventional ML libraries like TensorFlow or PyTorch are typically expected. Strong problem-solving abilities, effective communication, and a collaborative mindset help professionals stand out. Mastery of these skills and qualities is essential for tackling complex interdisciplinary challenges and driving innovation in this rapidly evolving field.

Is quantum machine learning a good career?

Quantum machine learning is an emerging field combining quantum computing and machine learning, with growing research and industry interest. Careers in this area typically require strong backgrounds in quantum physics, computer science, and programming skills, often involving specialized tools like quantum algorithms and hardware. As the technology advances, demand for experts in quantum algorithms and data analysis is expected to increase, making it a promising but highly specialized career path.

What cities in California are hiring for Quantum Machine Learning jobs?

Cities in California with the most Quantum Machine Learning job openings:

Infographic showing various Quantum Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $42,026 per year, or $20.2 per hour.

Machine Learning DevOps - Cloud and Compute Cluster - R&D Support

Pathway

Palo Alto, CA • On-site, Remote

$62 - $85/hr

Full-time

Re-posted 15 days ago


Job description

About Pathway

Pathway is shaking the foundations of artificial intelligence by introducing the world's first post-transformer model that adapts and thinks just like humans. 

Pathway's breakthrough architecture (BDH) outperforms Transformer and provides the enterprise with full visibility into how the model works. Combining the foundational model with the fastest data processing engine on the market, Pathway enables enterprises to move beyond incremental optimization and toward truly contextualized, experience-driven intelligence. The company is trusted by organizations such as NATO, La Poste, and Formula 1 racing teams.

Pathway is led by co-founder & CEO Zuzanna Stamirowska, a complexity scientist who created a team consisting of AI pioneers, including CTO Jan Chorowski who was the first person to apply Attention to speech and worked with Nobel laureate Goeff Hinton at Google Brain, as well as CSO Adrian Kosowski, a leading computer scientist and quantum physicist who obtained his PhD at the age of 20. 

The company is backed by leading investors and advisors, including TQ Ventures and Lukasz Kaiser, co-author of the Transformer ("the T" in ChatGPT) and a key researcher behind OpenAI's reasoning models. Pathway is headquartered in Palo Alto, California.

The opportunity

We are currently searching for a Machine Learning DevOps with experience in cloud and compute cluster management, scaling infrastructures, and Linux administration. 

Our development, ML training, and production environment is in the cloud, using several major cloud providers. We need support in managing and automating the processes, and scaling the infrastructure to growing team and production needs.

You Will
  • Optimize infrastructure for ML training and inference (e.g., GPUs, distributed compute).
  • Automate and maintain ML/LLM pipelines (data ingestion, training, validation, deployment).
  • Manage model versioning, reproducibility, and traceability.
  • Work with terabyte-large datasets. 
  • Implement ML-centric CI/CD practices.
  • Monitor model performance and data drift in production.
  • Collaborate with machine learning engineers, software engineers, and platform teams.

The role focuses on operationalizing machine learning models, ensuring scalability, reliability, and automation across the ML lifecycle.

Requirements

What We Are Looking For
  • Very good familiarity with Linux, shell scripts, and cluster configuration scripts as the basic work tool.
  • Proficiency in workload management, containerization and orchestration (Slurm, Docker, Kubernetes).
  • Solid grasp of CI/CD tools and workflows (GitHub Actions, Jenkins, Gitlab CI, etc.).
  • Cloud infrastructure knowledge (AWS, GCP, Azure) - especially in ML services (e.g., SageMaker Hyperpod, Vertex AI).
  • Familiarity with monitoring/logging tools (Grafana, CloudWatch, Prometheus, Loki).
  • Experience with infrastructure as code (Terraform, CloudFormation, cluster-toolkit).
  • Experience with ML pipeline orchestration tools (e.g., MLflow, Kubeflow, Airflow, Metaflow).
  • Programming skills in Python (with exposure to ML libraries like TensorFlow, PyTorch).
  • Experience with cluster, systems, and networks administration.
  • Willingness to learn.

This position holds a minimum requirement of a BSc in Computer Science or Information Technology.

We will generally favor candidates who have undertaken ambitious efforts in the past. For example, if you have made an accepted contribution to the Linux kernel, won an important bug bounty, supported an academic grid/cluster computing team in a scaling effort, or even won a sports championship, make sure to mention this in your application!

Benefits

Why You Should Apply
  • Intellectually stimulating work environment. Be a pioneer: you get to work with realtime data processing & AI.
  • Work in one of the hottest AI startups, with exciting career prospects. Team members are distributed across the world.
  • Responsibilities and ability to make significant contribution to the company' success
  • Inclusive workplace culture
Further details
  • Type of contract: Permanent employment contract
  • Preferable joining date: Immediate.
  • Compensation: based on profile and location.
  • Location: Remote work. Possibility to work or meet with other team members in one of our offices: Palo Alto, CA; Paris, France or Wroclaw, Poland. Candidates based anywhere in the EU, United States, and Canada will be considered.