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Machine Learning Assistant Jobs in California (NOW HIRING)

PlusAI

Machine Learning Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

Build an AI Assistant: Develop and deploy an internal AI chatbot that allows employees to query ... Machine Learning & NLP: Solid understanding of Large Language Models (LLMs), natural language ...

Apple

Machine Learning (MLOps) Engineer

Cupertino, CA · On-site

As an MLOps Engineer, you will be the backbone of our machine learning infrastructure, ensuring ... Comfort using LLM-based tools such as Claude, Gemini, or ChatGPT to assist with code generation ...

Turion Space

Machine Learning Engineer

Irvine, CA · On-site

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML ... Contribute to the deployment of MLOps processes and techniques * Assist in the development of ...

Apple

Machine Learning (MLOps) Engineer

Cupertino, CA · On-site

$212K - $318.40K/yr

Leverage AI coding assistants and LLM-based tools (e.g., Claude, Gemini, GitHub Copilot) to ... machine learning models in a production environment. Familiarity with model monitoring, drift ...

Elicit

Machine Learning Engineer

Oakland, CA · On-site +1

... role As a Machine Learning Engineer at Elicit, you'll build products and workflows that help ... Ability to use coding assistants effectively and thoughtfully, and has adapted their workflow to ...

Eightfold.ai

Machine Learning Engineer

Santa Clara, CA · On-site

$123.75K/yr

We are building cutting-edge agentic AI that can proactively assist users, automate complex ... Knowledge and passion in machine learning algorithms, Gen AI, LLMs, and natural language processing ...

PlusAI

Machine Learning Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

Strong foundation in classification and supervised learning. > Preferred Skills: Nice-to-Haves ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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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 Engineer Intern

Machine Learning Engineer Intern

PlusAI

Santa Clara, CA • On-site

$19 - $65/hr

Internship

Retirement

Posted 15 days ago

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World's Most Innovative Companies. Partners including TRATON GROUP's Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you're ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
Responsibilities:
  • Build an AI Assistant: Develop and deploy an internal AI chatbot that allows employees to query company knowledge and test results using natural language.
  • Implement RAG Architecture: Design and build a secure Retrieval-Augmented Generation (RAG) pipeline to pull contextual data from internal sources without compromising data privacy.
  • Develop Data Pipelines: Create automated pipelines to ingest, clean, and structure data from diverse sources, including internal documents, Slack conversations, and autonomous driving databases (bagdb, pluscene, and right-seater logs).
  • Fine-Tune Open-Source LLMs: Work with open-source models (such as Qwen) and fine-tune them to accurately understand and process company-specific terminology and AV testing metrics.
  • Generate Actionable Insights: Enable the system to synthesize complex data across simulation and road tests to answer questions about passing rates, test mileages, coverage gaps, and testing recommendations.

Required Skills:
  • Machine Learning & NLP: Solid understanding of Large Language Models (LLMs), natural language processing, and prompt engineering.
  • Python Programming: Strong proficiency in Python for machine learning workflows, scripting, and backend system integration.
  • Data Engineering Fundamentals: Experience building data extraction, transformation, and loading (ETL) pipelines, as well as handling both structured and unstructured data.
  • Familiarity with RAG: Core understanding of Retrieval-Augmented Generation workflows, text chunking, and vector embeddings.

Preferred Skills:
  • Open-Source LLM Experience: Hands-on experience deploying, fine-tuning, or quantizing open-source models (e.g., Qwen, LLaMA, Mistral) using frameworks like Hugging Face or vLLM.
  • Vector & Relational Databases: Experience working with vector databases (e.g., Milvus, Chroma, FAISS) as well as querying traditional SQL/NoSQL databases.
  • Autonomous Vehicle Domain Knowledge: Familiarity with autonomous driving data formats (e.g., ROS bags), simulation environments, or road testing metrics.
  • Chatbot Frameworks: Experience with LLM orchestration frameworks such as LangChain or LlamaIndex.
  • Data Security & Privacy: An understanding of best practices for deploying ML models locally or within secure, internally-hosted environments.

$19 - $65 an hour
Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience.
Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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