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Entry Level Machine Learning Jobs in Campbell, CA

Mathews Mechanical

Mechanic II/ Shop helper

Newark, CA · On-site

$25 - $28/hr

... machinery and mechanical equipment. This is an entry-level position intended to provide hands-on training and on-the-job learning to develop skills required for a career as a qualified Millwright.

Nvidia

GPU Compiler Engineer

Santa Clara, CA · On-site

Our Compiler team is responsible for constructing and emitting the highest performance GPU machine ... Be part of a team that is at the center of deep-learning compiler technology spanning architecture ...

Nvidia

GPU Compiler Engineer

Santa Clara, CA

Our Compiler team is responsible for constructing and emitting the highest performance GPU machine ... deep-learning compiler technology spanning architecture design and support through functional ...

Nuro

Associate Fleet Technician, Bay Area

Santa Clara, CA · On-site

$28.25 - $38/hr

The Associate Fleet Technician is a critical, entry-level technical role that provides the ... machinery. * Technical Troubleshooting Mindset: Enjoy solving problems that require learning and ...

Nuro

Associate Fleet Technician, Bay Area

Santa Clara, CA · On-site

$28.25 - $38/hr

The Associate Fleet Technician is a critical, entry-level technical role that provides the ... machinery. * Technical Troubleshooting Mindset: Enjoy solving problems that require learning and ...

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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 Sep 3, 2026, the average hourly pay for entry level machine learning in Campbell, CA is $20.21, according to ZipRecruiter salary data. Most workers in this role earn between $18.08 and $21.97 per hour, depending on experience, location, and employer.

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 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 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.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.
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What are the most commonly searched types of Machine Learning jobs in Campbell, CA?

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What job categories do people searching Entry Level Machine Learning jobs in Campbell, CA look for?

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What cities near Campbell, CA are hiring for Entry Level Machine Learning jobs?

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Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Campbell, CA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 27% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,045 per year, or $20.2 per hour.

Forward Deployed Engineer - Entry Level

ORDR, Inc.

Santa Clara, CA • On-site

Full-time

Re-posted 7 days ago

Job description

Ordr Inc., we secure the connected world by bringing visibility, intelligence, and control to every device - from life-saving hospital equipment to robotic arms on factory floors, ATMs in banks, and IoT systems in airports. Our AI-driven platform turns complex network data into real-time security insights for some of the world's largest and most mission-critical organizations.
We're seeking a Forward Deployed Engineer who brings a unique combination of technical coding expertise and customer understanding. You'll work directly with enterprises worldwide to deploy Ordr's AI solutions, ensuring successful adoption and delivering measurable impact.
What You'll Do
  • Collaborate with customers to understand their specific environments, data, and operational needs, translating them into effective AI deployment strategies.
  • Deploy, configure, and optimize Ordr's AI-powered platform to meet each customer's unique use cases - from hospitals and factories to banks and airports.
  • Combine your programming skills and AI/ML knowledge to tailor, automate, and enhance system integrations.
  • Work with Ordr's AI research and engineering teams to fine-tune models, validate results, and ensure production readiness.
  • Build and manage end-to-end ML pipelines for data ingestion, model deployment, and performance monitoring.
  • Present technical findings, results, and demos to both internal stakeholders and customer teams.
  • Gather feedback from real deployments to inform future product and AI model improvements.

Qualifications
Education:
  • BS or MS in Computer Science, Electrical Engineering, Data Science, Artificial Intelligence, or related field

Technical Skills:
  • Strong foundation in machine learning, data analysis, and applied AI.
  • Proficiency in Python and familiarity with key AI/ML libraries (PyTorch, TensorFlow, Scikit-learn).
  • Experience with AI development and deployment tools, including:
    • MLflow, Vertex AI, or AWS SageMaker for experiment tracking and deployment
    • Hugging Face or LangChain for LLMs and generative AI
    • Docker, Kubernetes, REST APIs, and CI/CD workflows
  • Understanding of networking, cybersecurity, or IoT data is a plus.
  • Comfort with scripting, debugging, and building automations in customer environments.

Soft Skills & Mindset
  • Unique blend of coding ability and customer empathy - able to translate complex technical concepts into real-world value.
  • Clear, confident communicator who enjoys collaborating with both engineers and customer stakeholders.
  • Highly motivated, adaptable, and eager to learn from fast-paced, real-world challenges.
  • Strong analytical mindset and hands-on problem-solving approach.
  • Passion for applying AI to make a tangible difference in large-scale, real-world systems.

Why Join Ordr
  • Work directly with global customers - from world-class hospitals to industrial and financial leaders - deploying AI solutions that protect their most critical assets.
  • Be part of a cross-functional AI team bridging research, engineering, and customer success.
  • See your work move from prototype to production and real-world impact.
  • Learn from top-tier AI and cybersecurity professionals.
  • Competitive salary, stock options, and comprehensive benefits.

Apply