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Zitara
BMS Algorithms Engineer
Over 1 year ago
About the Job
Company
In order to keep climate change to 1.5°C, we’ll need 30% of global GDP (all of energy generation and transportation) to run on batteries by 2035.
Zitara Technologies (YCombinator S20) builds predictive battery management software for transportation and energy customers with large deployments. Our customers operate >$100M deployments of batteries in satellites, EVs, and renewable energy storage installations.
Our team brings top researchers in physics-based battery algorithms together with seasoned software engineers to build safety-critical firmware and large scale machine learning systems. We bring with us decades of experience from companies like Tesla, Facebook, and Google.
Role
We're looking for a multidisciplinary software and simulation engineer who can draw from academic literature, practical engineering tools, and domain-specific data and models to design, analyze, and improve battery modeling and simulation software.
Zitara's software spans cutting-edge battery science, high-performance data infrastructure, complex modeling and learning systems, and safety-critical onboard firmware. We're looking for a software engineer who can work across these areas of expertise to build the algorithms behind our core technology.
In this role, you will work closely with our battery scientists and controls engineers to scale up our simulation and prediction software. You will also have the opportunity to work with our embedded team to adapt the algorithms you design for running in real-time battery management systems.
Responsibilities
Design, implement, and tune battery state estimation algorithms for predicting battery SoC, capacity fade, and power fade.
Collaborate with our battery science team to design and evaluate test plans that enable robust and accurate battery models.
Modeling
Design, tune, and implement real-time estimation algorithms (e.g. Kalman filters)
Work closely with embedded software engineers to help realize your algorithms in resource constrained environments.
Qualifications
5+ years working in BMS design or related work on battery state estimation
3+ years writing professional software in Python.
Solid understanding of the controls and estimation fundamentals such as signal processing, Kalman filtering, and related concepts from statistics and optimization.
BS, MS, or Ph.D in Electrical Engineering, Mechanical Engineering,, Chemistry / Chemical Engineering, Physics or other related engineering discipline.
Clear and effective written and interpersonal communication skills
Preferred Additional Qualifications
Experience programming in C or C++
Experience in high assurance systems development (eg, ISO26262 or DO178)
Note: this position may be filled by a candidate either remote or hybrid in-person in our SF office. In-person candidates will be preferred, and remote candidates will need to demonstrate superlative organizational and communication skills.
What We Offer
A full-time position, working from our office in San Francisco, CA or remotely.
Competitive pay. The salary range for this role is $140,000 - $170,000
Health, Dental, and Vision care for you and your family.
A 401k savings plan.
“Unlimited PTO” vacation policy.
Excellent colleagues that are interested in your happiness and growth.
Zitara is committed to building a diverse and inclusive team. Reports from LinkedIn and Hewlett Packard indicate that women are less likely to apply for positions due to perceived mismatches with listed qualifications. It's reasonable that this phenomenon extends to other underrepresented groups too. If you think you have what it takes but don't necessarily meet every single point listed, please apply - you could be exactly who we are looking for!
About the Company
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Zitara
Zitara Technologies builds battery management software for companies with large deployments. Customers across industries (EVs, satellites, renewable energy storage) rely on Zitara's cloud-ready embedded solutions for advanced battery management that precisely predict and manage the charge of every vehicle or fleet asset. With a precise charge plan, enterprises can minimize downtime, maximize the longevity of their battery systems, increase safety, and improve the predictability of their fleet operations.
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