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Entry Level Machine Learning Jobs in Novato, CA (NOW HIRING)

Skild AI

Research Engineer

San Francisco, CA

$100K - $300K/yr

We believe massive scale through data-driven machine learning is the key to unlocking these ... Base Salary Range: $100,000 - $300,000 USD Seniority Level: Entry level Employment Type: Full-time ...

SynergisticIT

data (Entry Level)

San Francisco, CA · On-site

$20 - $26.75/hr

From staffing to full implementation of projects we provide the highest quality IT Services. We Focus on Java/Full stack and Data Science/Machine learning/Python/AI candidates. You'll be responsible ...

Sidecar

Software Engineer - Fraud

San Francisco, CA · On-site

Strong engineering background coupled with experience around machine learning, pattern recognition, etc. * Code using primarily Python, Nodejs and PHP. * Work closely with other engineers on the team ...

Arnata

AI Engineer

San Francisco, CA

$150K - $250K/yr

At least a B.S. in Computer Science, Machine Learning, AI, or a related field. Exceptional ... Seniority level Entry level Employment type Full‑time Job function Engineering and Information ...

Windfall

Market Development Lead

San Francisco, CA · On-site

$105K - $150K/yr

This is not an entry-level role. We're looking for someone who has already proven they can generate ... Powered by best-in-class machine learning and artificial intelligence, Windfall activates insights ...

Windfall

Market Development Lead

San Francisco, CA · On-site

$105K - $150K/yr

This is not an entry-level role. We're looking for someone who has already proven they can generate ... Powered by best-in-class machine learning and artificial intelligence, Windfall activates insights ...

Windfall

Market Development Lead

San Francisco, CA

$105K - $150K/yr

This is not an entry-level role. We're looking for someone who has already proven they can generate ... Powered by best-in-class machine learning and artificial intelligence, Windfall activates insights ...

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Entry Level Machine Learning information

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How much do entry level machine learning jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for entry level machine learning in Novato, CA is $20.50, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $22.31 per hour, depending on experience, location, and employer.

What types of projects can an entry-level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or data science executives, often requiring advanced skills, extensive experience, and specialized knowledge. These positions usually involve leadership, strategic planning, and the development of complex AI systems, and they tend to be found in large tech companies or specialized AI firms.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

Which 3 jobs will survive AI?

Entry level machine learning roles are likely to persist as they require specialized knowledge in data analysis, programming, and domain expertise that AI tools currently cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and AI system trainers, are also expected to remain in demand. Developing skills in programming languages like Python and understanding of algorithms will enhance job security in this field.

How to get into machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, mathematics, and data analysis. Gaining skills through online courses, tutorials, and practicing with projects using tools like Python and libraries such as scikit-learn or TensorFlow can help build a portfolio. Earning certifications or completing relevant coursework can also improve job prospects for beginners.

What are entry level machine learning jobs?

Entry level machine learning jobs are positions designed for individuals just starting their careers in the field of machine learning. These roles typically involve working on data preparation, building and testing basic models, and assisting senior data scientists or engineers. Common job titles include Machine Learning Engineer, Data Analyst, or Junior Data Scientist. Requirements often include proficiency in programming languages such as Python, foundational knowledge of statistics, and experience with machine learning libraries. These jobs provide hands-on experience and mentorship to help new professionals grow their skills.

What Are Entry-Level Machine Learning Jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What jobs pay $4000 a week without a degree?

Entry-level machine learning roles typically do not pay $4000 a week without advanced skills or certifications. High-paying tech jobs often require specialized knowledge, experience, or degrees, but some freelance data scientists or AI consultants with strong portfolios can reach high earnings through project-based work. Most roles at this pay level generally demand experience or advanced training beyond entry-level positions.
More about Entry Level Machine Learning jobs
What cities near Novato, CA are hiring for Entry Level Machine Learning jobs? Cities near Novato, CA with the most Entry Level Machine Learning job openings:
Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Novato, CA as of July 2026, with employment types broken down into 1% Locum Tenens, 81% Full Time, 17% Part Time, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $42,650 per year, or $20.5 per hour.
Machine Learning Engineer, LLM Evals & Observability

Machine Learning Engineer, LLM Evals & Observability

Glean

San Francisco, CA • On-site

$200K - $300K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 7 days ago

Job description

About Glean:
Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry's most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.
At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean's agentic capabilities - AI agents that automate real work across teams by accessing the industry's broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
Recognized by Fast Company as one of the World's Most Innovative Companies (Top 10, 2025), by CNBC's Disruptor 50, Bloomberg's AI Startups to Watch (2026), Forbes AI 50, and Gartner's Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we're helping the world's largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
If you're excited to shape how the world works, you'll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
About the Role:
Building a great AI assistant is only half the battle - knowing whether it's actually great is the other half. Our team owns the measurement and quality layer that make Glean's Assistant and Agents reliably better over time: evaluation pipelines, quality evalsets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why. It's a rare combination of infrastructure engineering, applied ML, and direct product impact. If you care deeply about quality and want to build the systems that make it measurable, this role is for you.
You will:
  • Design and curate evaluation datasets - sampling strategies, query diversity, and golden sets that give reliable, representative coverage of real assistant behavior.
  • Build and maintain large-scale evaluation pipelines that measure assistant quality across thousands of real user queries.
  • Build LLM-powered judges that score metrics like correctness, completeness, and response quality, and align them against human judgment.
  • Evaluate new models and product changes before they ship - providing the quality signal that gates launches and prevents regressions.
  • Build observability infrastructure for AI agents: trace enrichment, data pipelines, and dashboards that make assistant behavior inspectable.
  • Close the loop between quality measurement and improvement using eval results, customer feedback, and techniques like automated prompt iteration to help drive concrete gains in assistant behavior.
  • Collaborate with engineers across the company to make evals a first-class part of how we ship.

About you:
  • 2+ years of software engineering experience with strong coding skills.
  • Strong backend fundamentals in Go and Python; comfortable with distributed data pipelines.
  • Experience working with LLM evaluation, reinforcement learning from human feedback, natural language processing, or other large systems involving machine learning.
  • Analytically rigorous - you think carefully about what offline metrics actually predict about real user experience.
  • Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company
  • You care about quality - not just in the systems you build, but in the product you're helping measure and improve.

Location:
  • This role is hybrid (3-4 days a week in one of our SF Bay Area offices)

Compensation & Benefits:
The standard base salary range for this position is $200,000 - $300,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
#LI-HYBRID
AI-First Mindset at Glean:
At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today - prior Glean experience isn't required.
Global Data Privacy Notice for Job Candidates and Applicants:
Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.
By clicking "Submit Application," I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.

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