1

Machine Learning Data Associate Jobs in Goleta, CA

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML ... Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU ...

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 ... Familiarity with RAG over structured business data and tool-using agents over API surfaces. * Prior ...

Sr. Machine Learning Engineer

Santa Barbara, CA · On-site +1

$116K - $159K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ... Familiarity with RAG over structured business data and tool-using agents over API surfaces. * Prior ...

Sr. Machine Learning Engineer

Santa Barbara, CA · On-site

$112K - $154K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ... Familiarity with RAG over structured business data and tool-using agents over API surfaces. * Prior ...

Build the training and fine‑tuning stack for small language models, including data pipelines, GPU orchestration, and evaluation. * Productionize research prototypes with SLOs, on‑call rotations ...

Deep Learning Algorithm Developer

Goleta, CA

$120K - $200K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... AI) / Machine Learning (ML) techniques. Experience in Computer Vision is desired for current openings. Our researchers apply AI/ML techniques to develop data processing automation solutions for ...

next page

Showing results 1-20

Machine Learning Data Associate information

See Goleta, CA salary details

$10

$20

$33

How much do machine learning data associate jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for machine learning data associate in Goleta, CA is $20.22, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $21.54 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How much do machine learning data associates make?

Machine Learning Data Associates typically earn between $40,000 and $70,000 annually, depending on experience, location, and the complexity of data tasks. Entry-level positions may start lower, while experienced associates working with large datasets or specialized tools can earn higher salaries.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, with opportunities for skill development and career growth in the tech industry.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What cities near Goleta, CA are hiring for Machine Learning Data Associate jobs?

Cities near Goleta, CA with the most Machine Learning Data Associate job openings:

Infographic showing various Machine Learning Data Associate job openings in Goleta, CA as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $42,052 per year, or $20.2 per hour.

Machine Learning Engineer

Quantum Machines

Santa Barbara, CA • On-site

Full-time

Re-posted 17 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