Entry Level Machine Learning Research Jobs
New grad machine learning research jobs welcome recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio of projects or internship work can outweigh a long resume. Most openings mix on-site and remote settings across Technology & Software, Artificial Intelligence, and Electronics & Hardware, with employers like Apple, Scale AI, and Google hiring at this level now.
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Showing 5 of 124+ Entry Level Machine Learning Research jobs
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 Machine Learning Research Jobs: Frequently Asked Questions
How do I get an entry level machine learning research job?
Employers hiring at the entry level look for hands-on evidence of skills: personal projects on GitHub, Kaggle competition results, or research conducted during a degree or internship. Familiarity with Python, PyTorch or TensorFlow, and foundational math such as linear algebra and probability gives candidates a real edge. A clear portfolio that shows you can frame a problem, build a model, and interpret results matters more than years on a resume at this stage.
Which companies hire entry level machine learning researchs?
Companies hiring entry level machine learning researchs right now include Apple, Scale AI, and Google, based on current listings on Migrate Mate as of July 2026. Hiring covers large technology firms with dedicated AI research labs, fast-growing startups building ML-powered products, and research-oriented organizations in academia-adjacent industries.
Are there remote entry level machine learning research jobs?
Yes, though availability varies by employer and role type. About 20% of entry level machine learning research openings are remote or hybrid as of July 2026, reflecting how common distributed research teams have become in this field. Some fully on-site roles still exist, particularly at labs that require access to specialized hardware or collaborative research environments.
Are these new grad machine learning research jobs?
Yes, the openings on this page include new grad, recent graduate, and junior machine learning research roles. A posting is generally new-grad friendly when it welcomes zero to two years of experience, accepts internship work or academic research in place of full-time history, or explicitly invites candidates with a strong portfolio rather than a long resume. Look for language like "new graduates encouraged to apply" or "0 to 2 years" as clear signals.
Which industries hire the most entry level machine learning researchs?
Entry Level machine learning research roles concentrate in Technology & Software, Artificial Intelligence, and Electronics & Hardware, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at the entry level because they are actively building or expanding AI research capabilities and need junior talent to support larger research teams and production model pipelines.