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Machine Learning Algorithms Jobs in California (NOW HIRING)

Machine Learning Engineers

San Jose, CA · On-site

$136K - $280K/yr

Design and build large-scale machine learning algorithms to deeply optimize e-commerce search engines such as ranking, query analysis, and correlation calculation and various business indicators of ...

Design and implement state-of-the-art machine learning algorithms for processing multimodal biosignals, including time series, spatial, and spectral data. * Build and optimize neural network ...

Design and implement state‑of‑the‑?? machine learning algorithms for processing multimodal biosignals, including time series, spatial, and spectral data. * Build and optimize neural network ...

... algorithms for Search&Discovery team. Apply machine learning/reinforcement learning to improve content understanding, computer vision, deep learning, language understanding and content ranking ...

... algorithms for Search&Discovery team. Apply machine learning/reinforcement learning to improve content understanding, computer vision, deep learning, language understanding and content ranking ...

... algorithms for Search&Discovery team. Apply machine learning/reinforcement learning to improve content understanding, computer vision, deep learning, language understanding and content ranking ...

Showing results 41-60

Machine Learning Algorithms information

What are machine learning algorithms?

Machine learning algorithms are computational methods that enable computers to learn patterns and make decisions or predictions from data without being explicitly programmed for each task. These algorithms can be classified into categories such as supervised learning, unsupervised learning, and reinforcement learning, each suited for different data and goals. Examples include decision trees, support vector machines, neural networks, and clustering algorithms. The choice of algorithm depends on the type of problem, the nature of the data, and the desired outcome.

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

To excel as a Machine Learning Algorithms Engineer, you need a solid background in mathematics, statistics, programming (especially Python or R), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow, PyTorch, or scikit-learn), data preprocessing tools, and cloud platforms is typically required, along with knowledge of version control systems. Strong analytical thinking, problem-solving abilities, and effective communication skills set top performers apart in this role. These skills and qualities are critical for designing robust models, collaborating with cross-functional teams, and translating complex data into actionable solutions.

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

As a Machine Learning Algorithms specialist, collaborating with cross-functional teams such as data engineers, software developers, and product managers can present challenges like aligning on project goals, communicating complex technical concepts to non-experts, and integrating models into existing systems. It's important to establish clear communication channels, define shared objectives early, and actively participate in iterative feedback cycles. These practices help ensure that machine learning solutions are both technically sound and aligned with business needs.

What is the difference between Machine Learning Algorithms vs Data Scientists?

AspectMachine Learning AlgorithmsData Scientists
CredentialsKnowledge of algorithms, programming, statisticsAdvanced degrees in data science, statistics, or related fields
Work EnvironmentDeveloping, testing, and tuning algorithmsAnalyzing data, building models, interpreting results
Industry UsageEmbedded within data science workflows and toolsLeading data analysis projects, decision-making

While machine learning algorithms are the core tools used by data scientists, the role of a data scientist encompasses understanding, applying, and interpreting these algorithms within broader data analysis and business contexts. Machine learning algorithms are technical components, whereas data scientists integrate these tools to derive insights and inform strategies.

What careers are there in machine learning algorithms?

Careers in machine learning algorithms include roles such as machine learning engineer, data scientist, research scientist, and AI developer. These positions typically require skills in programming, statistics, and familiarity with tools like Python, TensorFlow, or PyTorch, and often involve developing models, analyzing data, and deploying AI solutions.
Infographic showing various Machine Learning Algorithms job openings in California as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 59% Full Time, 38% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer

Sunnyvale, CA • On-site

$150K - $450K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago


Job description

About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.
As part of our team, you'll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.
The Role
As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world challenges, pushing the boundaries of artificial intelligence research. You will collaborate with cross-functional teams to deploy scalable solutions, contributing to MBZUAI's mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide.
Key Responsibilites
  • 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.

Academic Qualifications
  • Minimum: Bachelor's degree or equivalent practical experience.
  • Preferred: Master's degree or PhD in Computer Science or related technical field.

Professional Experience - Minimum
  • 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.

Professional Experience - Preferred
  • 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.

$150,000 - $450,000 a year
Visa Sponsorship
This position is eligible for visa sponsorship.
Benefits Include
*Comprehensive medical, dental, and vision benefits
*Bonus
*401K Plan
*Generous paid time off, sick leave and holidays
*Paid Parental Leave
*Employee Assistance Program
*Life insurance and disability