Entry Level Sr Staff Machine Learning Engineer Jobs
New grad sr staff machine learning engineer jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship work can matter more than a long resume. Most openings mix on-site, remote, and hybrid settings across Technology & Software, Artificial Intelligence, and Electronics & Hardware, with employers like Apple, Google, and Scale AI hiring at this level now.
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MOUNTAIN VIEW, CALIFORNIA, UNITED STATES. SAN FRANCISCO, CALIFORNIA, UNITED STATES. NEW YORK CITY, NEW YORK, UNITED STATES
FULL-TIME
SOFTWARE ENGINEERING
5053
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you!
This role follows a hybrid work schedule and reports to an Engineering Manager.
You will:
- Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning.
- Use simulation creatively and mine real world driving logs to measure driving performance.
- Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes.
- Champion code health and best practices in a large and complex code base.
- Analyze data and make recommendations on how to improve metric quality and interpretability.
- Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions.
You have:
- BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area
- Strong self-motivation to navigate complex systems and pursue open-ended problems to completion
- 2-3 years of industry experience with
- Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL
- Performing statistical analyses
- Building data processing pipelines
- Writing, reviewing, and merging code following industry standards for code health and maintainability
- Quant/data fluency is a top requirement
We prefer:
- Experience coding in C++
- Experience with ML
- Experience with A/B experiment infrastructure
- Experience building and validating metrics to measure quality in complex systems
- Exposure to ad-hoc data analysis tools for rapid modeling and prototyping
- Experience working in the AV industry
#LI-Hybrid
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
MOUNTAIN VIEW, CALIFORNIA, UNITED STATES. SAN FRANCISCO, CALIFORNIA, UNITED STATES. NEW YORK CITY, NEW YORK, UNITED STATES
FULL-TIME
SOFTWARE ENGINEERING
5053
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you!
This role follows a hybrid work schedule and reports to an Engineering Manager.
You will:
- Develop signals to measure the performance and driving qualities of the Waymo driver, using a range of techniques including statistics, math, physics, algorithms and machine learning.
- Use simulation creatively and mine real world driving logs to measure driving performance.
- Design and implement methods to make a stronger connection between onboard software changes and simulated outcomes.
- Champion code health and best practices in a large and complex code base.
- Analyze data and make recommendations on how to improve metric quality and interpretability.
- Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions.
You have:
- BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area
- Strong self-motivation to navigate complex systems and pursue open-ended problems to completion
- 2-3 years of industry experience with
- Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL
- Performing statistical analyses
- Building data processing pipelines
- Writing, reviewing, and merging code following industry standards for code health and maintainability
- Quant/data fluency is a top requirement
We prefer:
- Experience coding in C++
- Experience with ML
- Experience with A/B experiment infrastructure
- Experience building and validating metrics to measure quality in complex systems
- Exposure to ad-hoc data analysis tools for rapid modeling and prototyping
- Experience working in the AV industry
#LI-Hybrid
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
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Entry Level Sr Staff Machine Learning Engineer Jobs: Frequently Asked Questions
How do I get an entry level sr staff machine learning engineer job?
Employers hiring at this level look for candidates who can demonstrate applied skills through projects, coursework, or internships rather than years of experience. A portfolio showing model development, data pipelines, or published code repositories gives you a concrete edge. Bootcamp graduates and career changers with relevant project work are competitive. Focus on roles that list internships or coursework as acceptable experience.
Which companies hire entry level sr staff machine learning engineers?
Companies hiring entry level sr staff machine learning engineers right now include Apple, Google, and Scale AI, based on current listings on Migrate Mate as of June 2026. At this level, you'll find a mix of tech companies, AI-focused startups, and large enterprises building out machine learning teams who are willing to develop candidates with strong foundational skills.
Are there remote entry level sr staff machine learning engineer jobs?
Yes, though availability varies by employer and team. About 27% of entry level sr staff machine learning engineer openings are remote or hybrid as of June 2026, making this a field where new grads can access opportunities without relocating. Many hybrid roles are structured to support junior team members with in-person collaboration a few days per week.
Are these new grad sr staff machine learning engineer jobs?
Yes, these listings include new grad, recent graduate, and junior roles. A posting is new-grad friendly when it welcomes zero to two years of experience, counts internships or research as qualifying background, or lists a portfolio as an acceptable substitute for a long work history. Searching for roles that mention entry level or junior signals you're in the right range.
Which industries hire the most entry level sr staff machine learning engineers?
Entry Level sr staff machine learning engineer roles concentrate in Technology & Software, Artificial Intelligence, and Electronics & Hardware, based on current listings on Migrate Mate as of June 2026. These sectors tend to drive hiring at this level because they are actively scaling machine learning capabilities and need candidates who can contribute to production models and data infrastructure from an early career stage.