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Machine Learning Engineer Intern Jobs in Pittsburg, CA

Sift

Machine Learning Engineer

San Francisco, CA · On-site

$160 - $230/hr

As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won't just train models in isolation; you will build end-to-end pipelines ...

Clay Labs

Machine Learning Engineer

San Francisco, CA · On-site

$180 - $240/hr

Machine Learning Engineer @ Clay Clay's ambition is to build a self-learning revenue engine : a product that gets smarter every time someone uses it. This means data, ML, and AI are at the heart of ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $400K/yr

About the role We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You'll play a central role in ...

Firecrawl

Machine Learning Engineer

San Francisco, CA · On-site

$210K - $240K/yr

Machine Learning Engineer You'll build the ML behind Firecrawl - the models and the systems that serve them. That starts with search: training and shipping the ranking and relevance models for one of ...

Workday

Machine Learning Engineer III

Pleasanton, CA

About the Role As a Machine Learning Engineer on the AI Platform team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate with other engineers to ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA

$123K - $169K/yr

We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash ...

Conduit

Machine Learning Engineer

San Francisco, CA · On-site

Conduit builds autonomous factories through a single data abstraction layer across every machine ... Translate customer needs into clean engineering briefs for the SF team. Build relationships with ...

Capable

Machine Learning Engineer

San Francisco, CA · On-site

$150K - $240K/yr

About the Role You will build machine-learning systems that remove real bottlenecks from drug discovery and development. The role spans research and engineering: identifying valuable problems ...

Capable

Machine Learning Engineer

San Francisco, CA · On-site

$150 - $230/hr

About the Role You will build machine-learning systems that remove real bottlenecks from drug discovery and development. The role spans research and engineering: identifying valuable problems ...

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All JobsMachine Learning Engineer Intern JobsMachine Learning Engineer Intern Jobs in Pittsburg, CA

Machine Learning Engineer Intern information

See Pittsburg, CA salary details

$28.3K

$47.3K

$97.8K

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

As of Sep 7, 2026, the average yearly pay for machine learning engineer intern in Pittsburg, CA is $47,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,100.00 and $51,100.00 per year, depending on experience, location, and employer.

What is a machine learning engineer intern?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What do machine learning engineer interns do?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

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

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are popular job titles related to Machine Learning Engineer Intern jobs in Pittsburg, CA?

For Machine Learning Engineer Intern jobs in Pittsburg, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Intern jobs in Pittsburg, CA look for?

The top searched job categories for Machine Learning Engineer Intern jobs in Pittsburg, CA are:

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Cities near Pittsburg, CA with the most Machine Learning Engineer Intern job openings:

Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Pittsburg, CA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $47,333 per year, or $22.8 per hour.

Machine Learning Engineer

Sift

San Francisco, CA • On-site

$160 - $230/hr

Other

Re-posted 18 days ago

Job description

The Role:

As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won’t just train models in isolation; you will build end-to-end pipelines that extract signals, train custom models per merchant, and serve predictions at production scale with low latency. You will work on an automated machine learning ecosystem that dynamically recalibrates models based on streaming global telemetry data.

What You'll Do:
  • Model Development & Refinement: Design, build, and deploy online machine learning models (including ensemble methods, deep learning, transformer architectures and graph-based models) to catch evolving fraud vectors in real time.
  • Feature Engineering at Scale: Engineer high-frequency time-series features from over 1 trillion behavioral events, optimizing for low-latency signal extraction and pattern recognition.
  • Production MLOps: Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained models.
  • System Optimization: Write high-performance code to minimize scoring latency at runtime, ensuring our core ML services scale seamlessly across distributed databases.
  • Collaborative Innovation: Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutions.
What We Are Looking For (Requirements):
  • Experience: 4+ years of professional experience building and deploying large-scale machine learning models into high-traffic production environments.
  • Solid Programming Foundations: Strong proficiency in Java or Scala (for our production backend) as well as Python (for data analysis and model prototyping).
  • Distributed Systems & Big Data: Practical experience with Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, and working with NoSQL data stores like Bigtable.
  • Strong Mathematical Foundations: Deep understanding of statistical modeling, probability, and standard machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks, and Clustering techniques).
  • System Design Mentality: Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (GCP).
Bonus Points (Preferred Qualifications):
  • Experience explicitly in the fraud detection, risk mitigation, or cyber-security domains.
  • Deep knowledge of streaming architectures (e.g., Apache Kafka).
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and model prototyping

Please note: final stage candidates may be asked to travel for in-person final round interviews.

Let's build it together:

At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.

—This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy

A little about us:

Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.

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