About Ghost

At Ghost, our mission is to make self-driving for everyone. We build autonomous driving software for automakers, based on a breakthrough in artificial intelligence that finally makes highway autonomy safe and scalable for the consumer car market.

Ghost helps automakers reimagine the car of the future with a complete autonomy solution that can be fully customized and continuously upgraded, delivering a car that keeps getting better year after year.

At Ghost, we are responsible for both invention and productization – not only solving complex problems with novel technology but making sure that it can scale to millions of drivers on the road. It’s a bold undertaking, but one that makes for constant learning, real-world impact, and fulfilling work. Together, we are a small, multi-disciplinary team tackling one of the hardest challenges in technology today.

Ghost was founded in 2017 by John Hayes and Volkmar Uhlig. Before Ghost, John co-founded Pure Storage, taking the company public in 2015.

Ghost has over a hundred employees across its headquarters in Mountain View and additional offices in Dallas, Detroit, and Sydney. Ghost has raised over $200 million from investors including Mike Speiser at Sutter Hill Ventures, Keith Rabois at Founders Fund, and Vinod Khosla at Khosla Ventures.

Learn more at https://ghostautonomy.com.

The Role

As a Machine Learning Engineer at Ghost, you will be part of a broader Model Engineering team responsible for building and testing the models that literally drive our vehicles. Operating on the noisy data of a real-world environment, the problems you face will be complex and open-ended, and the solutions you create have the potential for enormous impact. With a proven founding team and compelling plan, Ghost knows where it is going - but how it gets there will be up to you.

Requirements:

Professional experience working with real-world, physical data
Strong knowledge of machine learning, data engineering, deep learning frameworks, and related testing techniques
Ability to fine tune GPT models
A track record of having shipped models and code into production
Strong programming skills in object-oriented languages (functional programming is a plus), including ability to debug and optimize code

Benefits

Medical, Vision and Dental coverage (PPO, HMO, and HSA options available; 100% premium coverage of several PPO and HMO plans for employees)
401(k) plan
Life Insurance

Compensation

Compensation for this role consists of a base salary and an options grant, with the base salary expected to range from $175,000 to $275,000+. Individual compensation will be commensurate with the candidate’s experience.

Ghost is committed to equal employment opportunity. We will not discriminate against employees or applicants for employment on any legally‑recognized basis [“protected class”] including, but not limited to: veteran status, uniform service member status, race, color, religion, sex, national origin, age, physical or mental disability or any other protected class under federal, state or local law.

Ghost Autonomy

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Machine Learning Engineer