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No Experience Machine Learning Jobs in San Ramon, CA

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Hands-on experience training and fine-tuning large language models (LLMs) and vision-language ...

... Experience Cloud, Document Cloud, Lightroom and creative marketplace by enabling the world's best ... If this role does not have Colorado listed as a hiring location, no specific application window ...

The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ... Experience with video understanding, tracking, pose estimation, robotics, or real-world sensor ...

Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable * Experience with machine learning frameworks such as Scikit ...

PhD in computer science, machine learning, computational neuroscience, or related fields (or equivalent industry experience). * Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and ...

They are seeking a Machine Learning Engineer to train and deploy critical models for their core ... Required : • You have 2+ years of experience with training, fine tuning, and evaluating ML models ...

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No Experience Machine Learning information

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$15

$25

$34

How much do no experience machine learning jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for no experience machine learning in San Ramon, CA is $25.50, according to ZipRecruiter salary data. Most workers in this role earn between $22.02 and $28.46 per hour, depending on experience, location, and employer.

What kinds of projects or learning opportunities can I expect in a no experience machine learning role?

In a no experience machine learning role, you will often start by assisting with data preprocessing, exploring datasets, and supporting more experienced engineers on real-world projects. You may also participate in internal trainings, mentorship programs, or hands-on workshops to build up your technical skills. Collaboration is common, so expect regular team meetings and opportunities to pair-program or seek guidance from senior colleagues. Over time, as you gain proficiency, you may be assigned small-scale projects or research tasks, providing a clear pathway to take on more complex responsibilities. This supportive environment is designed to help you gradually develop expertise and advance your career in machine learning.

What are the key skills and qualifications needed to thrive in the no experience machine learning position, and why are they important?

To thrive in an entry-level machine learning role with no prior experience, you should possess a solid understanding of mathematics (especially statistics and linear algebra), basic programming knowledge (often in Python), and a willingness to learn. Familiarity with popular data science tools and frameworks such as scikit-learn, TensorFlow, or online courses and certifications in machine learning is advantageous. Curiosity, problem-solving abilities, and effective communication are soft skills that help you work collaboratively and adapt to new challenges. These attributes are important because they enable quick learning, help you contribute to team projects, and support your growth in a rapidly evolving technical field.

What are the most commonly searched types of Machine Learning jobs in San Ramon, CA? The most popular types of Machine Learning jobs in San Ramon, CA are:
What job categories do people searching No Experience Machine Learning jobs in San Ramon, CA look for? The top searched job categories for No Experience Machine Learning jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for No Experience Machine Learning jobs? Cities near San Ramon, CA with the most No Experience Machine Learning job openings:
Infographic showing various No Experience Machine Learning job openings in San Ramon, CA as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $53,046 per year, or $25.5 per hour.

Machine Learning Engineer

Nace AI

Palo Alto, CA • On-site

Full-time

Re-posted 22 days ago


Job description

Role Overview:
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-functional teams to identify opportunities where ML can drive product value, architect robust model-centric systems, and ensure their seamless integration into real-world applications. The role requires a strong balance between theoretical understanding and engineering execution, with a focus on building reliable, maintainable, and high-impact AI-driven features that align with Nace.AI's strategic objectives.
Key Responsibilities:
  • Design, build, and maintain end-to-end ML systems, including synthetic data pipelines, model training, debugging, and performance evaluation.
  • Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model generalization and efficiency.
  • Improve existing Nace.AI models by incorporating advancements from recent ML research.

Qualifications:
  • Hands-on experience training and fine-tuning large language models (LLMs) and vision-language models (VLMs), including practical work with pre-training, instruction tuning, and alignment techniques (GRPO,RLHF/DPO/PPO).
  • Hands-on Experience with Deep Learning Models, especially Transformers.
  • Ability to translate cutting-edge research from papers into clean, production-ready code (Paper to Code).
  • Proven experience scaling inference infrastructure for LLMs/VLMs, including expertise in model serving frameworks like vLLM, TGI.
  • Proficient in Python with a strong track record of building substantial projects.
  • Solid foundation in computer science fundamentals (data structures, algorithms, design patterns).
  • BS degree in CS or related technical field.
  • Solid Experience with ML frameworks and libraries (PyTorch, TensorFlow).
  • Self-starter comfortable working in a fast-paced, dynamic environment.

Preferred Qualifications:
  • MS/PhD in CS or related technical field.
  • Familiarity with data processing stacks such as Spark and Airflow.
  • Experience with multi-node GPU training.
  • Contributor to open-source ML projects.
  • Deep knowledge in Linear Programming.
  • Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation, quantization, deployment optimization).
  • Experienced in inference time optimization, deep understanding of LLM serving optimizations for LLMs/VLMs.
  • Hands on experience with quantization techniques (AWQ, GPTQ, FP8/GGUF).