Offer summary

Qualifications:

B.S. in Computer Science or related field, or equivalent experience., Experience developing and maintaining LLM-based conversational applications., Proficiency in PyTorch or other machine learning frameworks., Strong programming skills in Python and a low-level language like Rust or C++., Familiarity with CAD software and distributed systems..

Key responsabilities:

Develop and implement conversational interfaces using LLMs for user experience.

Iterate and fine-tune ML models based on user feedback and data.

Design and optimize a large scale distributed ML system and algorithms.

Curate and maintain large annotated datasets for training ML models.

Job description

About Us

We're on a mission to revolutionize the CAD industry by developing the world's most advanced hardware design infrastructure and tools. Mechanical CAD is in the dark ages, and hardware demands have outpaced today’s hardware design infrastructure. The industry is due for a refresh, and we're laying the foundation for a modern hardware design toolkit so that you can create new design tools never before possible.

We are headquartered in Los Angeles, CA with both a local and remote, globally-distributed team. We were founded and incubated by Embedded Ventures in 2021.

About You

We’re looking for curious, innovative, and ambitious self-starters to join our lean and growing team to help us bring our mission to life. We think you’ll thrive on our team if you’re:

Excited about making an impact on the ground floor of something big!
Curious at your core, with an eagerness to learn and do things differently
Customer-focused, always thinking about ways to improve the user experience
Able to operate autonomously and work asynchronously, while also being an effective team player

About The Role

We’re looking for a Machine Learning Software Engineer to help design and implement Zoo’s foundational machine learning systems to enable the next generation of hardware engineering. In this role, you’ll apply cutting edge techniques in machine learning to support the end-to-end development of ML models and features that improve our users' experience. The ideal candidate will have prior experience developing a large scale distributed ML system, and ideally has an understanding of hardware design and manufacturing related processes with knowledge of the relevant data required.

What You’ll Do

Develop and implement robust conversational interfaces using LLMs for a seamless user experience
Continuously iterate and fine-tune models to improve accuracy, relevance, and user experience based on data and user feedback
Help design, develop, optimize, and debug a large scale distributed ML system and algorithms
Improve upon existing ideas in generative AI and develop unique solutions to the problems we’re solving in hardware design
Curate and maintain large annotated datasets to train ML models at a massive scale
Interact with CAD models and modeling/shape setups
Experiment with various proof of concepts and ideas for our use cases

What You’ll Need

B.S. Computer Science or a related field, or equivalent professional experience
Demonstrated experience successfully developing, deploying and maintaining an LLM-based conversational copilot application
Professional experience with PyTorch, or any of the current machine learning frameworks
Experience with CAD software and processes, and modeling/shape algorithms
Strong programming skill with Python, and one low-level language such as Rust or C++
Experience with Git
Prior experience working on a production system
Familiarity with distributed systems

What We Offer

Competitive compensation & equity packages
Medical, Dental, and Vision coverage for you and your dependents
6% 401K match (for US-based employees)
Flexible vacation policy (for US-based employees)
Home office stipend & wifi reimbursement to set you up for success working remotely
Pet insurance reimbursement for your animal friends

Zoo is proud to be an equal opportunity employer. We’re committed to equal employment opportunity for all, regardless of background, identity, or status.

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