Battery Modeling Engineer

Job Description

Job Description

About Zipline

Zipline is the world's largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world's largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products.

Our customers include the world's largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we've built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people's lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.

You will be part of Zipline's Systems Modeling Team, which develops physics-based models used to architect, optimize, and validate Zipline's aircraft hardware and operational systems. Battery performance, charging behavior, and lifetime directly affect how reliably the fleet can serve customers.

You will own end-to-end battery modeling from cell electrochemistry through pack electro-thermal behavior and fleet software integration. Your work will guide cell selection, hardware operating limits, charging decisions, and the validated energy models used in fleet optimization.

• Own cell-level models across electrochemical and equivalent-circuit fidelities to evaluate performance, fast charging capability, degradation, and lifetime.
• Define Zipline's cell electrochemistry roadmap and lead cell benchmarking and selection with internal teams and cell vendors.
• Design and analyze characterization and validation campaigns, including EIS, HPPC, OCV, and cycle and calendar aging studies.
• Develop pack-level electro-thermal models that predict electrical and thermal non-uniformity during high-power operation and charging.
• Build state-estimation and controls-oriented algorithms for SOC, SOH, SOE, SOP, and aging-aware charging-current limits.
• Integrate validated battery and energy models into simulation and operational software that informs fleet charging, turnaround, battery-health, and aircraft-energy decisions.

• 5+ years of professional battery-modeling experience, or a PhD plus 2 years, with a focus on electrochemical modeling.
• Deep knowledge of cell electrochemistry, heat transfer, thermodynamics, electrical circuits, numerical methods, and optimization.
• Hands-on experience with SPM, SPMe, P2D, equivalent-circuit models, and battery degradation mechanisms.
• Experience planning, running, or interpreting battery characterization and validation testing, including EIS, HPPC, OCV, and aging studies.
• Proficiency in at least one of MATLAB, Python, Julia, C++, or Rust.
• Ability to communicate complex model behavior and datasets clearly and work closely with mechanical, electrical, test, and systems-modeling engineers.
• Advanced degree in mechanical, electrical, chemical engineering, physics, computational science, or a related field is preferred; familiarity with PyBaMM is a plus.

Preferred Qualifications:

• Advanced degree (MS or PhD preferred) in Mechanical Engineering, Electrical Engineering, Chemical Engineering, Physics, Computational Science, or related field.
• Familiarity with PyBaMM or similar electrochemical battery modeling frameworks.
• Experience with battery degradation and lifetime modeling.
• Experience developing battery state estimation algorithms.

The starting cash range for this role is $130,000 - $165,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Zipline 's Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.