Staff Machine Learning Research Scientist
Staff Machine Learning Research Scientist
Posted on :
05-04-2025
Employer Active
1 Vacancy
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Yearly Salary
$ 228800 - 343200
Vacancy
1 Vacancy
Posted on :
05-04-2025
Job Description
At Toyota Research Institute (TRI) were on a mission to improve the quality of human life. Were developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility weve built worldclass teams in HumanCentered AI Energy & Materials Human Interactive Driving Large Behavioral Models and Robotics.
TRIs Harmonious Communities Department within our HumanCentered AI (HCAI) Division has an immediate opening for a Staff AI Research Scientist interested in our core topic domain of social wellbeing and the future of work. We are looking for someone with expertise in and enthusiasm for machine learning research (e.g. model architecting simulations complex datasets).
We are particularly keen to talk with people who have interest or experience in using realworld humanlevel data to model prefactuals and counterfactuals (e.g. multiagentbased modeling reinforcement learning causal inference ML RDM AI Graph Neural Networks). We are launching a new project space and want a colleague who can help define and build this trajectory.
Our mission is to use research to foster Toyotas global mission of wellbeing and happiness for all and this challenge motivates everything we do. We are a coordinated team of behavioral scientists ML researchers and humancomputer interaction experts. The person who accepts this opportunity must have a strong interest in collaborating across all of these domains. Additionally this role will work with teams across Toyota to design and pilot technologies that help us to better understand the social dynamics within and around our workplaces. Candidates should be selfstarting and interested in making contributions within a multidisciplinary team project.
Responsibilities
- Collaborate crossfunctionally with specialists in multiple fields as well as university partners to research and develop technology that models emergent properties in social systems
- Stay current on the stateoftheart in Machine Learning theories practice and software
- Collaborate with scientists in the Harmonious Communities Department to shape and craft our research program and to communicate research to Toyota collaborators and stakeholders
- Publish findings in academic journals and/or conferences (e.g. KDD ICWSM WWW ACL EMNLP NAACL AAMAS CSCW)
- Contribute to technology transfer of research throughout Toyota
Qualifications
- 7 years of experience with PhD in computer science machine learning computational social science or related field with a broad knowledge of machine learning approaches and theory. We encourage candidates to apply even if they dont meet every qualification. We value diverse experience and are open to learning more about how your unique skills could contribute to the team.
- Experience with simulation / prefactual / counterfactual approaches (multiagentbased modeling GNNs Robust Decision Modeling AI etc.
- Experience with architecting ML systems across diverse data sources (text timeseries data tabular data etc. including familiarity with cloud platforms (AWS GPC or Azure) virtualization (Docker) and orchestration (Kubeflow Metaflow).
- Proficiency in ML frameworks (e.g. scikitlearn PyTorch TensorFlow Keras) and tools for big data analysis (e.g. Databricks Sagemaker SQL Spark).
- Ability to communicate complex concepts clearly across different audiences
- Strong interpersonal skills enthusiastic collaborator and great teammate
- Heavy interest in research to facilitate social wellbeing
Bonus Qualifications
- Experience with time series modeling and data analysis
- Ability to balance multiple projects including shortterm targeted analyses and novel innovative projects that may span several years
- Familiarity with humancentered research (e.g. behavioral data science computational social science humancomputer interaction) including qualitative and/or quantitative methods such as experiments and user studies
The pay range for this position at commencement of employment is expected to be between$228800and$343200/year for Californiabased roles; however base pay offered may vary depending on multiple individualized factors including market location jobrelated knowledge skills and experience. Note that TRI offers a generous benefits package (including 401(k) eligibility and various paid time off benefits such as vacation sick time and parental leave) and an annual cash bonus structure. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
Please reference thisCandidate Privacy Noticeto inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute Inc. or its subsidiaries including Toyota A.I. Ventures GP L.P. and the purposes for which we use such personal information.
TRI is fueled by a diverse and inclusive community of people with unique backgrounds education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all without regard to an applicants race color creed gender gender identity or expression sexual orientation national origin age physical or mental disability medical condition religion marital status genetic information veteran status or any other status protected under federal state or local laws.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance we will consider qualified applicants with arrest and conviction records for employment.
Required Experience:
Staff IC
Employment Type
Full-Time
Key Skills
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