Location(s): Santa Clara, CA
Job Schedule: Full-time, Hybrid
Education Requirement: Bachelor's Degree
Sponsorship: No
Come Drive Innovation with UsWith a focus on vehicle electrification, intelligent mobility, and data-driven engineering, Nissan is advancing next-generation EV platforms and battery technologies. We are committed to leveraging software, data, and system-level intelligence to maximize battery performance, safety, and lifetime value.
At Nissan, our people are what drive our success. We are seeking a highly skilled battery systems expert to help shape the future of intelligent battery management through the integration of advanced analytics, AI, and engineering expertise. The Battery R&D team in Silicon Valley is focused on combining battery engineering, large-scale data analytics, and artificial intelligence to enable next-generation battery intelligence.
A Day in the LifeAs an SME Researcher, you will apply deep battery systems expertise to support the development of agentic AI-driven battery intelligence. This role serves as a key bridge between battery engineering, data science, and AI development, translating physical battery system behavior into intelligent decision-making frameworks.
Key responsibilities include:
- Define battery system states, including State of Charge (SOC), State of Health (SOH), thermal conditions, and system constraints.
- Interpret and formalize BMS logic and operational boundaries.
- Capture safety and control constraints within system representations.
- Translate battery behavior into structured computational frameworks.
Agentic AI Development
- Design AI systems capable of making autonomous battery-related decisions.
- Define state, action, and reward structures for intelligent decision-making frameworks.
- Incorporate physics-based constraints into AI models.
- Support the development of adaptive and self-optimizing battery management strategies.
Data & Analytics
- Analyze large-scale vehicle and telematics datasets.
- Identify real-world usage patterns and battery degradation behaviors.
- Develop and utilize Python-based data analysis workflows.
- Support predictive modeling and simulation environments.
Cross-Functional Integration
- Collaborate closely with BMS, data science, and AI teams.
- Align physical battery constraints with AI-based decision logic.
- Bridge the gap between embedded battery systems and cloud-based analytics platforms.
Strategic Contributions
- Contribute to Nissan's next-generation battery intelligence roadmap.
- Identify high-impact applications for agentic AI technologies.
- Translate technical findings into actionable business and engineering outcomes.
Who We're Looking ForWe are seeking a technically curious and innovative battery systems expert who thrives at the intersection of engineering, analytics, and artificial intelligence. The ideal candidate possesses strong Battery Management System knowledge and can translate complex battery behavior into data-driven, AI-enabled solutions.
Required:- Bachelor's degree plus 5-10 years of relevant experience OR Master's degree and 2-5 years of relevant experience OR Ph.D. and 0-2 years of relevant experience.
- Degree in Engineering, Computer Science, or a related technical field.
- Strong understanding of battery behavior, including SOC, SOH, thermal characteristics, and operating constraints.
- Solid knowledge of Battery Management Systems (BMS), including estimation methods, control logic, and safety concepts.
- Proficiency with Python and data analysis tools such as NumPy, Pandas, and related libraries.
- Experience working with large-scale datasets, including vehicle, telematics, IoT, or similar data sources.
- Ability to abstract physical systems into computational and analytical frameworks.
- Strong problem-solving skills and cross-functional collaboration capabilities.
Desired:- Experience with artificial intelligence and machine learning technologies.
- Knowledge of reinforcement learning, agent-based systems, or sequential decision-making frameworks.
- Familiarity with vehicle and telematics data analysis.
- Experience working with cloud-based data platforms.
- Background in battery degradation analysis, modeling, or lifecycle prediction.
- Experience with simulation environments, digital twins, or virtual validation frameworks.
- Demonstrated innovation through patents, publications, or product contributions.
- Experience working in research-focused or highly ambiguous environments.
Nissan is committed to fostering an inclusive workplace where employees can thrive and contribute their best work. We are proud to be an Equal Opportunity Employer and welcome applicants from all backgrounds.
What You'll Look Forward to at Nissan: Career Growth and Continuous Learning Opportunities: Benefit from diverse career paths, cross-departmental moves, and innovative learning platforms. Enhance your skills through seminars, leadership training, and tuition reimbursement programs, all while playing a vital role in shaping the future of transportation. From day one, you'll have the support to tackle challenges and contribute to impactful solutions across our organization.
Rewards: Be supported with a Comprehensive Benefits Package, including medical, mental health, parental leave, retirement savings & unique Nissan perks, including discounts on lease vehicles as part of our Employee Lease Program and a Vehicle Purchase Program (VPP). For more information, access our Nissan Benefits Overview Guide.
Built for Your Best: ;list=PLki2k0CDxrPe8V6WmEeEdhj1fosRD-JQa
Nissan is committed to a drug-free workplace. All employment is contingent upon the successful completion of drug and background screenings in accordance with Nissan policies and in compliance with federal, state, and local laws, including the California Fair Chance Act and the Los Angeles County Fair Chance Ordinance. Nissan will consider qualified candidates with arrest or conviction records for employment in a manner consistent with these laws.
It is Nissan's policy to provide Equal Employment Opportunity (EEO) to all persons regardless of race, gender, military status, disability, or any other status protected by law. Candidates for this position must be legally authorized to work in the United States and will be required to provide proof of employment eligibility at the time of hire; Nissan uses E-Verify to validate employment eligibility.
NISSAN FOR EVERYONEPeople are our most valuable assets, and diversity and inclusion are the key to maximizing the power of each individual member of our team. When everyone belongs, the power of NISSAN is undeniable. Our Corporate Diversity Initiative aims to improve business results by ensuring that our workplace and core businesses meet the unique needs of our employees and customer base.
Nissan is committed to creating a culture where everyone belongs and employees, customers, and partners feel respected, valued, and heard. We have over 10 Business Synergy Teams (BSTs) across the U.S. and Canada that connect employees - with shared characteristics or interests - build allies, and foster a company culture where all employees feel supported and included.
Nissan also values inclusion in all areas of our business as we strive to mirror the diversity of our customer base and the communities where we do business. We are committed to procuring innovative goods and services, retailing our products and communicating from a diverse perspective which will help us continue to offer our customers competitively designed, market-driven products.
Join us as we carry our commitment to diversity and inclusion into the future.
Santa Clara California United States of America
Salary Range:
$134,042.00 - $230,590.00
Salary Range Estimate: Annual Salary: (Minimum to Maximum of Salary Range noted here). This compensation range represents the minimum and maximum base salary rates at Nissan for jobs assigned to this particular grade level. Please note that it is uncommon for an employee to be placed at either end of the range. Rather, an employee's actual base salary generally may fall somewhere in between and reflect the employee's unique skills, work experience, education, work location, and market norms. Additionally, pay may be based on comparisons to the base salary rates of other employees with similar backgrounds working in comparable roles.
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