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Machine Learning Engineer New Grad Jobs in Santa Barbara, CA

AppFolio, Inc.

Sr. Machine Learning Engineer

Santa Barbara, CA · On-site +1

$116K - $159K/yr

It enables a new generation of intelligent capabilities across our products, including Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

AppFolio

Sr. Machine Learning Engineer

Goleta, CA

$112K - $154K/yr

It enables a new generation of intelligent capabilities across our products, including Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

AppFolio

Staff Machine Learning Engineer

Goleta, CA · On-site

It enables a new generation of intelligent capabilities across our products, including Realm-X ... Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML ...

AppFolio

Sr. Machine Learning Engineer

Santa Barbara, CA

$112K - $154K/yr

It enables a new generation of intelligent capabilities across our products, including Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

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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All JobsMachine Learning Engineer New Grad JobsMachine Learning Engineer New Grad Jobs in Santa Barbara, CA

Machine Learning Engineer New Grad information

See Santa Barbara, CA salary details

$35K

$143.3K

$215.3K

How much do machine learning engineer new grad jobs pay per year?

As of Aug 5, 2026, the average yearly pay for machine learning engineer new grad in Santa Barbara, CA is $143,278.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,900.00 and $172,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer new grad?

A Machine Learning Engineer New Grad job is an entry-level role for recent graduates specializing in machine learning and artificial intelligence. It typically involves developing, training, and deploying machine learning models, working with large datasets, and optimizing algorithms for performance. New grads in this role often collaborate with data scientists, software engineers, and product teams to integrate models into applications. Employers look for proficiency in programming (Python, TensorFlow, PyTorch), a strong foundation in ML concepts, and experience with data processing. This role provides an opportunity to gain hands-on industry experience and grow technical skills in real-world applications.

What are the key skills and qualifications needed to thrive in the machine learning engineer new grad position, and why are they important?

To thrive as a Machine Learning Engineer New Grad, a strong background in computer science, statistics, and mathematics, often supported by a relevant degree, is essential. Familiarity with programming languages like Python or Java, machine learning frameworks (such as TensorFlow or PyTorch), and basic knowledge of data tools and cloud platforms is typically required. Effective problem-solving, eagerness to learn, and clear communication help new grads excel when collaborating on projects and learning from senior team members. These skills and qualities are vital for adapting quickly, contributing to team goals, and building a successful foundation in this fast-evolving technical field.

What are the typical day-to-day tasks of a machine learning engineer new grad?

As a Machine Learning Engineer New Grad, your daily tasks often include collecting and preprocessing data, developing and testing machine learning models, and analyzing model performance. You may work closely with data scientists and software engineers to integrate models into production systems and address real-world business problems. Participating in team meetings, code reviews, and collaborative projects is common, providing opportunities to learn best practices and receive mentorship. This hands-on, varied workload helps you quickly build technical and collaborative skills early in your career.

What are popular job titles related to Machine Learning Engineer New Grad jobs in Santa Barbara, CA? For Machine Learning Engineer New Grad jobs in Santa Barbara, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer New Grad jobs in Santa Barbara, CA look for? The top searched job categories for Machine Learning Engineer New Grad jobs in Santa Barbara, CA are:
What cities near Santa Barbara, CA are hiring for Machine Learning Engineer New Grad jobs? Cities near Santa Barbara, CA with the most Machine Learning Engineer New Grad job openings:
Machine Learning Engineer New Grad jobs near you
Infographic showing various Machine Learning Engineer New Grad job openings in Santa Barbara, CA as of July 2026, with employment types broken down into 50% Full Time, 12% Part Time, and 38% Contract. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $143,278 per year, or $68.9 per hour.

Machine Learning Engineer

Quantum Machines

Santa Barbara, CA • On-site

Full-time

Re-posted 7 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

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