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Machines Jobs in California (NOW HIRING)

ALIGN PRECISION

Machinist II - 5-6 Axis Machines

Walnut, CA · On-site

$21.25 - $29/hr

Monitors the feed and speed of machines. Measures and examines completed products for defects. May also perform complex and varied machining operations in prototype experimental activities. Sets up ...

Align Percision

Machinist II - 5-6 Axis Machines

Walnut, CA

$21.25 - $29/hr

Monitors the feed and speed of machines. Measures and examines completed products for defects. May also perform complex and varied machining operations in prototype experimental activities. Sets up ...

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How much do machines jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for machines in California is $26.67, according to ZipRecruiter salary data. Most workers in this role earn between $24.18 and $30.38 per hour, depending on experience, location, and employer.

What is the difference between Machines vs Equipment Operators?

AspectMachinesEquipment Operators
Required CredentialsMay include technical certifications or training in machineryOften requires certification or licensing specific to operating heavy equipment
Work EnvironmentFactories, construction sites, manufacturing plantsConstruction sites, industrial settings, outdoor environments
Industry UsageManufacturing, construction, miningConstruction, roadwork, landscaping
Job FocusDesign, maintenance, and repair of machinesOperating and controlling heavy equipment

Machines refer to the equipment used in various industries, while Equipment Operators are responsible for operating that machinery. Both roles often require specific certifications and are common in construction, manufacturing, and industrial sectors. Understanding the distinction helps job seekers target the right roles based on skills and interests.

What cities in California are hiring for Machines jobs? Cities in California with the most Machines job openings:
Infographic showing various Machines job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, 2% Temporary, 2% Contract, and 2% Nights. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $55,464 per year, or $26.7 per hour.

Machine Learning Engineer

Quantum Machines

Santa Barbara, CA • On-site

Full-time

Re-posted 14 days ago

Job description

Description
Quantum Machines (QM) is a global leader in quantum computing control systems. Through our pioneering hardware and software solutions based on instruction-based quantum control, we're revolutionizing how quantum computers are built and controlled. As we stand at the forefront of exponential growth in quantum computing, we're assembling an elite team that actively shapes the evolution of quantum technologies.
We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.
You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.
Responsibilities:
  • Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
  • Develop real-time parameter steering for calibration during QEC and between circuits.
  • Develop and maintain agentic frameworks for autonomous system control and calibration.
  • Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
  • Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
  • Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.

Requirements
  • PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related field. 4+ years of relevant experience
  • Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one of: deep learning, reinforcement learning, agentic AI
  • Strong Python proficiency, including scientific or systems-oriented codebases
  • Solid software engineering fundamentals (architecture, Git workflows, testing, code review)
  • Proven track record of taking ML from prototype to deployment under real-world constraints - non-stationary data, expensive evaluations, or safety-critical action spaces. Robotics, online control, autonomous vehicles, or hardware-in-the-loop ML all transfer well
  • Strong problem-solving skills and customer-focused mindset; ability to work independently and in multidisciplinary teams
  • Proven software development track record and excellent technical communication skills
  • Familiarity with quantum computing concepts - qubit calibration, randomized benchmarking, QEC, optimal control- advantage
  • Experience with sim-to-real, multi-objective RL, or meta-learning- advantage

Apply