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Machine Learning Engineer Data Science Intern Jobs in California

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist. * Proficiency across topics in machine learning and statistics.

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist. * Proficiency across topics in machine learning and statistics.

Data Science Intern

Menlo Park, CA · On-site

$8.6K - $10K/mo

Led by machine learning pioneers who built some of the most successful ad systems at Google ... As a Data Science Intern in DSA, you will drive performance improvement and cost efficiency in our ...

D. in Computer Science, Data Science, or a related field • Strong programming skills in Python or R • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) • Knowledge of ...

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ...

You will collaborate closely with data scientists, backend engineers, and product teams to turn data into measurable product impact. Job Title Machine Learning Engineer Job ID 20985 Location Work ...

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ...

Showing results 21-40

Machine Learning Engineer Data Science Intern information

What does a machine learning engineer data science intern do?

A Machine Learning Engineer Data Science Intern assists in developing and implementing machine learning models and data-driven solutions under the guidance of experienced professionals. The role typically involves data preprocessing, feature engineering, model training, and evaluation. Interns often collaborate with teams to solve real-world problems using statistical analysis and programming. They gain hands-on experience with popular tools and frameworks, such as Python, TensorFlow, and scikit-learn. This internship helps build foundational skills for a future career in machine learning and data science.

What kinds of projects does a machine learning engineer data science intern typically work on, and how are they supported by their team?

As a Machine Learning Engineer Data Science Intern, you will often be assigned to real-world projects such as building predictive models, cleaning and preprocessing data, and assisting with the deployment of machine learning solutions. You’ll collaborate closely with senior data scientists, software engineers, and sometimes product managers, receiving guidance during code reviews and regular team meetings. The environment is typically fast-paced and supportive, encouraging learning through mentorship and hands-on experience. Interns are expected to communicate their findings clearly and contribute to the team’s problem-solving efforts.

What are the key skills and qualifications needed to thrive as a machine learning engineer data science intern, and why are they important?

To thrive as a Machine Learning Engineer Data Science Intern, you need a strong background in mathematics, statistics, and programming (typically Python), supported by coursework or a degree in computer science, data science, or a related field. Familiarity with tools and libraries like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is commonly required. Problem-solving skills, intellectual curiosity, and effective communication make a candidate stand out in collaborative and dynamic environments. These skills are vital for analyzing complex datasets, building reliable models, and clearly communicating insights that drive data-driven decision-making.

Machine Learning Engineer

San Mateo, CA • On-site, Remote

Full-time

Re-posted 9 days ago


Job description

Company Description
PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems.
Job Description
We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.
Responsibilities:
  • Build and deploy the ML pipelines that power PatternAI's machine learning platform.
  • Manage MLOps infrastructure to monitor and optimize models.

Qualifications
Experience:
  • 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.
  • Proficiency across topics in machine learning and statistics.
  • Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)
  • Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.
  • Familiarity with CNNs, RNN, LSTMs, and the latest research trends.
  • Experience implementing, deploying, and maintaining production machine learning systems.
  • Experience monitoring and optimizing model performance.
  • Experience with Linux, Docker and AWS, and basic development operations.
  • Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

Additional Information
About PatternAI
PatternAI is an early stage startup that is growing rapidly and recently closed a successful round of venture funding. We are emerging from stealth and with an exciting series of machine learning products and a rapidly growing number of enterprise customers.
All your information will be kept confidential according to EEO guidelines.