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Machine Learning Engineer Opt Jobs in California

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team. The successful individual in this role will focus on applying ...

Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the overall tech lead of a single AI/Machine Learning team, responsible for the tech design and tech health ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Two Dots is looking for our 2nd Machine Learning Engineer, who will work closely with the CTO and the Staff ML Engineer. In this role you will design, develop, and deploy machine learning solutions ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144.30K - $190.30K/yr

We are not able to provide visa sponsorship (including H-1B, OPT, or other employment-based visas ... As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how ...

Senior Machine Learning Engineer

San Francisco, CA

$144.30K - $190.30K/yr

We are not able to provide visa sponsorship (including H-1B, OPT, or other employment-based visas ... As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how ...

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with ...

... machine learning/deep learning systems, computer vision, graphics, computational imaging applications.Experience with Pytorch. MS/PhD in computer vision, electrical, optical or computer engineering ...

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of data-driven and ML-powered solutions for semiconductor R&D, test, and operations teams. In this role ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

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Machine Learning Engineer Opt information

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What cities in California are hiring for Machine Learning Engineer Opt jobs? Cities in California with the most Machine Learning Engineer Opt job openings:
Infographic showing various Machine Learning Engineer Opt job openings in California as of May 2026, with employment types broken down into 90% Full Time, 4% Part Time, 3% Temporary, and 3% Contract. Highlights an 100% Physical job distribution.

Full-time

Posted 11 days ago


Job description

Job Summary:
MBZUAI is a dedicated research lab for building, understanding, using, and risk-managing foundation models. As a Machine Learning Engineer, you will develop and implement innovative machine learning models, collaborate with cross-functional teams, and contribute to MBZUAI's mission of driving impactful AI discoveries.
Responsibilities:
• Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.
• Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.
• Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.
Qualifications:
Required:
• Bachelor’s degree or equivalent practical experience.
• 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
• Excellent problem-solving and troubleshooting skills to address complex technical challenges.
• Effective communication and collaboration skills to work with cross functional teams.
Preferred:
• Master's degree or PhD in Computer Science or related technical field.
• 2 years of experience with improving performance during large scale data processing.
• Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
• Excellent data analysis skills.
Company:
Official account of Mohamed bin Zayed University of Artificial Intelligence. Dedicated to research, innovation, and empowering brilliant minds in AI. Founded in 2019, the company is headquartered in Abu Dhabi, ARE, with a team of 51-200 employees. The company is currently Growth Stage.