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Machine Learning Intern Remote Jobs in Santa Clara, CA

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

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Machine Learning Intern Remote information

See Santa Clara, CA salary details

$29.9K

$50K

$103.4K

How much do machine learning intern remote jobs pay per year?

As of Aug 7, 2026, the average yearly pay for machine learning intern remote in Santa Clara, CA is $50,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,200.00 and $54,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a machine learning intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What does a machine learning intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.
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Machine Learning Intern Remote jobs near you

AI & Machine Learning Engineer

Sustainable Talent

Santa Clara, CA • On-site, Remote

$90 - $130/hr

Other

PTO

Re-posted 21 days ago

Job description

Sustainable Talent is partnering with Nvidia a global leader who's been transforming computer graphics, PC gaming, and accelerated computing for over 25 years. We are looking for Generative AI Security Engineer to support our client's team based out of in Santa Clara, CA with remote/ hybrid work options. 

This is a full-time (W-2) contract role. We offer competitive pay $90/hr - $130/hr based on factors like experience, education, location, etc. and provide full benefits, PTO, and amazing company culture!

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams, focused on AI Safety for LLMs, including multi-lingual, multi-modal, and reasoning models.  We value expertise in data science paired with a robust data engineering foundation.   This role is directed at assessing, and improving the safety and inclusivity of our LLM models in a scalable fashion.  We seek someone proficient in programming and scripting for comprehensive data manipulation, analysis, and model fine-tuning.  We believe in proactive problem-solving, minimal supervision, and being exceptional teammates who collaborate, think, and learn as one unit. Let's make a difference together!

What you'll be doing:

  • Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness. These LLM models can be txt-to-txt or multimodal-to-txt.
  • Develop datasets for training LLM models with SFT and RL techniques, for Content Safety, ML Fairness, Security and more.
  • Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems.
  • Define and track key metrics for responsible LLM behavior and usage.
  • Follow the best practices of automation, monitoring, scale, safety.
  • Contribute to our repositories and develop safety tools to help ML teams be more effective.
  • Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets.
  • Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.
  • Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

What we need to see:

  • Bachelor's or Master's Degree in Computer Science or related field or equivalent experience.
  • 2+ years of work experience as a Machine Learning Engineer or Deep Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions.
  • Strong programming skills in languages such as Python. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Proficiency in data manipulation, analysis, and visualization using tools like NumPy and pandas.
  • Deep understanding of machine learning algorithms, statistical models, and data structures.
  • Familiarity with software development practices and version control systems (e.g., Git).
  • Good at problem solving and analytical ability.
  • Excellent collaboration and communication skills.

Ways to stand out from the crowd:

  • Experience with GenAI Security including Prompt Injection Stability, Model Extraction, Confidentiality/Data Extraction, Integrity, Availability and Adversarial Robustness.
  • Experience with one or more of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.
  • Experience with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs  (Vision Language Model) or any-to-text
  • Experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance.
  • Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research and publication experience.

Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.

Apply