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Junior Machine Learning Jobs in California (NOW HIRING)

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Adobe, Inc.

Machine Learning Engineer

San Jose, CA · On-site

$96K - $128K/yr

Mentor junior engineers and help grow the team's technical depth. What You Need to Succeed Required Qualifications * Master's or Ph.D. in Computer Science, Machine Learning, or a related technical ...

Adobe

Machine Learning Engineer

San Jose, CA

$96K - $128K/yr

Mentor junior engineers and help grow the team's technical depth. What You Need to Succeed Required Qualifications * Master's or Ph.D. in Computer Science, Machine Learning, or a related technical ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Provide guidance and mentorship to junior engineers, fostering a culture of learning and growth ... Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch)

Hive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... Provide mentorship to and help onboard junior ML engineers * Collaborate cross-functionally with ...

Hive

Senior Machine Learning Engineer

San Francisco, CA

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... Provide mentorship to and help onboard junior ML engineers * Collaborate cross-functionally with ...

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Junior Machine Learning information

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise with tools like TensorFlow or PyTorch, and may require multiple years of experience and relevant certifications.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of specialized experience and a strong track record of impactful projects.

Can I get an AI job with no experience?

Entry-level machine learning roles, such as Junior Machine Learning positions, often require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is beneficial, candidates can improve their chances by completing relevant online courses, building projects, and gaining familiarity with tools like Python and TensorFlow.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and machine learning engineers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
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 Junior Machine Learning jobs in California? For Junior Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning jobs in California look for? The top searched job categories for Junior Machine Learning jobs in California are:
What cities in California are hiring for Junior Machine Learning jobs? Cities in California with the most Junior Machine Learning job openings:
Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in California as of July 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution.

Machine Learning Manager

Hive

San Francisco, CA

$180K - $250K/yr

Full-time

Re-posted 2 days ago

Job description

About Hive 

Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!

Machine Learning Manager

In order to execute our vision, we're constantly growing our machine learning team.  We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential.  We value hard workers who have no qualms working with terabyte-scale datasets. We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
  • Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
  • Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
  • Participate in products technical design and architecture
  • Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
  • Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
  • Implement and manage security protocols such as training, code review, and best practices
  • Own and manage the risk and security of your business function in coordination with the Security Team
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
  • Undergraduate or graduate degree in computer science or similar technical field
  • 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
  • Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
  • 2+ years experience managing machine learning teams
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
  • Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
  • Have experience collaborating with product managers and labeling team in delivering model improvements
Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Hive and we hope to meet you soon!

The current expected base salary for this position ranges from $180,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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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