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Machine Learning Assistant Jobs in California (NOW HIRING)

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

$122.80K - $184.20K/yr

Principal Duties and Responsibilities: • Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model efficiency software tools with new features and ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Aquabyte

Machine Learning Engineer

San Francisco, CA · On-site

$130K - $170K/yr

Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Advantest

Machine Learning Engineer

San Jose, CA · On-site

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of ... practices. * Assist in implementing model monitoring, retraining workflows, and documentation.

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Machine Learning Assistant information

What are the key skills and qualifications needed to thrive as a Machine Learning Assistant, and why are they important?

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

What are some common challenges a Machine Learning Assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What is a Machine Learning Assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.
What are the most commonly searched types of Machine Learning jobs in California? The most popular types of Machine Learning jobs in California are:
What are popular job titles related to Machine Learning Assistant jobs in California? For Machine Learning Assistant jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Assistant jobs in California look for? The top searched job categories for Machine Learning Assistant jobs in California are:
What cities in California are hiring for Machine Learning Assistant jobs? Cities in California with the most Machine Learning Assistant job openings:
Machine Learning Assistant jobs near you
Machine Learning Engineering Intern

Machine Learning Engineering Intern

Qeexo, Co.

San Clemente, CA • On-site

$25/hr

Full-time

Posted 14 days ago

Job description

Machine Learning Engineer Intern TDK SensEI San Clemente, CA
This position is for our San Clemente, CA office - only apply if you are based there or willing to relocate
At TDK SensEI, we are transforming how industrial customers utilize and interact with sensor data. We specialize in developing advanced AI solutions capable of running directly on edge devices. By processing data locally, TDK SensEI enhances real-time decision-making, privacy, security, and cost efficiency. Our offerings include automated machine learning tools, AI-powered condition-based monitoring systems, and various sensor devices optimized for low latency and power consumption. Collaborating with leading global companies, we empower teams to effortlessly devise and implement machine learning solutions for industrial applications, all without the need for coding.
We are looking for a machine learning intern who loves working with sensor data, loves developing novel algorithms, and has strong curiosity about developing new GenAI-based ML applications. You will be working with a highly capable team of machine learning engineers and software engineers and will have the opportunity to make a meaningful impact on important new product development.
As a Machine Learning Engineer Intern, your responsibilities will include:
1. Assist in Model Development: Collaborate with senior engineers to develop and train machine learning models tailored for edge devices.
2. Data Collection and Preprocessing: Gather and preprocess data from various sensors and sources to ensure high-quality inputs for AI models.
3. Prototype Development: Develop and test prototypes for new Gen AI-based use cases, ensuring they meet performance and reliability standards.
4. Performance Evaluation: Conduct experiments to evaluate the performance of AI models and edge solutions, identifying areas for improvement.
5. Collaboration: Work closely with cross-functional teams, including machine learning and software engineers, to integrate AI solutions into prototype systems.
Ideal Candidate
. Signal processing and machine learning (most likely in EE major)
. Computer vision (most likely in CS major)
. Language model (most likely in CS major)
• Deep knowledge of statistical and machine learning approaches and problem domains
• Machine Learning/Computer Science/Electrical Engineering background with strong coding ability and proficiency with Python or other OOP language
• Proven success with multiple ML/AI/classification projects (research papers, open-source implementations, etc.)
• Expertise in one or more specific areas of research: automated machine learning, anomaly detection, condition monitoring, predictive maintenance, neural nets, deep learning, signal processing, digital imaging, ensemble learning, and system identification
• Experience working with GenAI applications
• Comfortable working in a terminal environment, writing scripts (Bash/Python) to process data and implement algorithms
Skills & Requirements:
• Master's or PhD student
• Python or other modern OOP language (proficient)
• Data Structures and Algorithms (proficient)
• Deep Learning (proficient)
• Data Structures and Algorithms (familiar)
• Experience with Docker and AWS (familiar)
• US Work Authorization required
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About Qeexo

Sourced by ZipRecruiter

Industry

It services

Company size

1 - 10 Employees

Headquarters location

Mountain View, CA, US

Year founded

2012

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