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Machine Learning Ai Jobs in California (NOW HIRING)

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

  • Medical

  • Dental

  • Vision

Poesis is the AI-native investment firm running autonomous agents that predict markets, construct ... About the Role At Poesis, machine learning and artificial intelligence open the door to improved ...

Staff Machine Learning Engineer

Mountain View, CA · On-site

$162K - $342K/yr

  • Medical

  • Retirement

  • PTO

Omnissa is the first AI-driven digital work platform, built to support flexible, secure, work-fro ... As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems ...

Machine Learning Engineer Location: San Francisco, CA Sponsorship: No Relocation: No Industry ... You will implement state-of-the-art deep learning techniques to help develop innovative AI products.

Agentic AI Engineer

Santa Clara, CA · On-site

$135K - $162K/yr

... machine learning models for classification, regression, NLP, or computer vision tasks. • Write ... AI/ML solutions into applications and workflows. • Conduct experiments, evaluate model ...

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $190K/yr

Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges. * Write clean, well-documented, and production-quality Python ...

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

  • Medical

  • Dental

  • Vision

  • PTO

... AI platform. Key Responsibilities Machine Learning Research & Development * Design, train, and ... optimize custom deep learning models that understand CAD workflows and generate intelligent ...

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges. * Write clean, well-documented, and production-quality Python ...

Showing results 41-60

Machine Learning Ai information

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

To thrive as a Machine Learning AI Engineer, you need a strong background in mathematics, statistics, programming (typically Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow and PyTorch, as well as cloud platforms and data processing tools, is essential, and certifications in these areas can be advantageous. Strong problem-solving, communication, and collaboration skills help you effectively translate business needs into technical solutions and work well within multidisciplinary teams. These skills ensure you can develop robust AI models that address real-world challenges and deliver meaningful business impact.

What is a machine learning AI?

A Machine Learning AI specialist is a professional who develops algorithms and models that enable computers to learn from and make predictions or decisions based on data. They work with large datasets, train and evaluate machine learning models, and often collaborate with software engineers and data scientists to integrate AI solutions into products and services. Their work is crucial in fields like natural language processing, computer vision, and predictive analytics, helping organizations automate tasks, gain insights, and improve efficiency.

What are some common challenges faced when collaborating with cross-functional teams as a machine learning AI?

As a Machine Learning AI professional, you’ll often collaborate with data engineers, software developers, and product managers. A common challenge is bridging the gap between complex AI models and practical business requirements, ensuring your solutions are both technically sound and aligned with user needs. Effective communication is key, as you’ll need to explain technical concepts to non-technical stakeholders and adapt your models based on feedback. Building trust and fostering a collaborative environment will help ensure successful project outcomes and foster continual learning.

What is the difference between Machine Learning Ai vs Data Scientist?

AspectMachine Learning AiData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with programming and algorithmsDegree in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDeveloping algorithms, training models, deploying AI systemsAnalyzing data, creating reports, interpreting results
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

Machine Learning Ai focuses on developing and deploying AI algorithms and models, while Data Scientists analyze and interpret data to inform business decisions. Both roles often collaborate but have distinct focuses within the data and AI ecosystem.

What cities in California are hiring for Machine Learning Ai jobs?

Cities in California with the most Machine Learning Ai job openings:

Infographic showing various Machine Learning Ai job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer, AI Safety

Nvidia

Santa Clara, CA • On-site

Full-time

Posted 19 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies


Job description

NVIDIA is in a unique position: we are developing AI-based products across multiple domains, and we collaborate with many interesting AI companies as partners and customers. Ensuring the highest Content Safety possible reduces exposure to inappropriate material. Preventing Bias and Discrimination is essential to both protect individual rights and achieve the best quality of results, including accuracy and completeness of information. By prioritizing safety and fairness, we can ensure that LLMs benefit everyone and contribute to a better future for all.
Our team also works in the area of safety for generative models for language, robustness, and explainability. Our LLMs are a growing area of AI products, including models and services, and we are committed to ensuring that they are used safely and responsibly.We are looking for a talented Machine Learning Engineer to work on Product Security, Content Safety,ML Fairness and Robustness efforts for LLMs across all of our research and production engineering teams.In this role, you'll have the opportunity to take on innovative problems in machine learning, particularly focused on safety for multi-modal LLMs. This role is directed at assessing, quantifying, and improving the safety and inclusivity of our LLM models in a scalable fashion.

What you'll be doing:

  • Develop the datasets and models for training and evaluating models and end-to-end systems for Content Safety, ProdSec, Robustness and ML Fairness.

  • Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems using LLMs like RAGs.

  • Define and track key metrics for responsible LLM behavior and usage.

  • Follow the best MLOps practices of automation, monitoring, scale and safety.

  • Contribute to the MLOps platform and develop safety tools to help ML teams be more effective.

  • Collaborate with other engineers, data scientists, and researchers to develop and implement solutions to content safety and ML fairness challenges.

What we need to see:

  • Master's or PhD in Computer Science, Electrical Engineering or related field - or equivalent experience.

  • Minimum of 2+ years of work experience in developing and deploying machine learning models in production.

  • Strong understanding of machine learning principles and algorithms.

  • Hands-on programming experience in python and in-depth knowledge of machine learning frameworks, like Keras or PyTorch.

  • Background in one or more of the following broader areas for 1+ years: Content Safety, ML Fairness, Robustness, AI Model Security, or related areas.

  • Experience working in a range of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.

  • Practice working with large multi-modal datasets and multi-modal models.

  • Good at problem-solving and analytical ability.

  • Excellent collaboration and communication skills.

  • Demonstrates behaviors that build trust: humility, transparency, respect, and intellectual honesty.

Ways to stand out from the crowd:

  • Skilled with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs (vision-language models) or any-to-text

  • Proven experience with multimodal and/or multilingual content safety, legal, and regulatory compliance.

  • Knowledge of robustness, including hallucinations, digressions, and generative misinformation.

  • Experience withGenAI security, including prompt stability, model extraction, confidentiality/data extraction, integrity, availability, and adversarial robustness.

  • Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research, and publication experience.

With highly competitive salaries and a comprehensive benefits package, Nvidia is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working with us and our engineering teams are growing fast in some of the hottest state of the art fields: Deep Learning, Artificial Intelligence, and Large Language Models. If you're a creative engineer with a real passion for robust and enjoyable user experiences, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 15, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993