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Contract Google Machine Learning Engineer Jobs in Goleta, CA

AppFolio

Staff Machine Learning Engineer

Goleta, CA

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML ... Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible ...

AppFolio

Sr. Machine Learning Engineer

Goleta, CA

$112K - $154K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Sr. Machine Learning Engineer

Santa Barbara, CA

$112K - $154K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Toyon

Deep Learning Algorithm Developer

Goleta, CA

$120K - $200K/yr

Toyon has openings for researchers and developers to solve challenging real-world problems using Artificial Intelligence (AI) / Machine Learning (ML) techniques. Experience in Computer Vision is ...

Toyon

AI/ML Software Engineer

Goleta, CA

$120K - $200K/yr

Toyon is seeking highly qualified AI/ML Software Engineer candidates to develop software in the Python or C++ languages in support of Artificial Intelligence (AI) / Machine Learning (ML) applications.

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How much do contract google machine learning engineer jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for contract google machine learning engineer in Goleta, CA is $52.80, according to ZipRecruiter salary data. Most workers in this role earn between $44.38 and $54.71 per hour, depending on experience, location, and employer.
What job categories do people searching Contract Google Machine Learning Engineer jobs in Goleta, CA look for? The top searched job categories for Contract Google Machine Learning Engineer jobs in Goleta, CA are:
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Infographic showing various Contract Google Machine Learning Engineer job openings in Goleta, CA as of July 2026, with employment types broken down into 52% Full Time, 31% Part Time, 1% Temporary, and 16% Contract. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution, with an average salary of $109,818 per year, or $52.8 per hour.

Machine Learning Engineer

Quantum Machines

Santa Barbara, CA • On-site

Full-time

Re-posted yesterday

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

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