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Salary
$180k – $240k per year
Location
In office (San Mateo)
Seniority
Senior · 6+ years exp
Employment
Full-Time
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Hestus is AI-powered CAD software that speeds up hardware development.

Location: San Mateo, CA

About Us: We are Hestus, and we build AI-powered CAD to speed up the hardware development process. Our team is small, scrappy, and growing fast. We are looking for a versatile and enthusiastic Machine Learning Engineer to join us. If you enjoy wearing multiple hats and are passionate about technology, we want to hear from you!

Responsibilities:

  • Design, train, and evaluate custom machine learning models and embeddings behind our AI-powered CAD.
  • Own the entire data pipeline: from data wrangling and curation through to the model training framework.
  • Build and improve our training and evaluation infrastructure, including experiment tracking, metrics, and reproducibility.
  • Take models from prototype to production: deployment, monitoring, and iteration based on real-world performance.
  • Collaborate with cross-functional teams to turn product needs into machine learning solutions and ship new features.
  • Write clean, efficient Python, and participate in code reviews, testing, and debugging.
  • Stay current with the latest machine learning research (LLMs, embeddings, and representation learning) and bring new ideas to the team.

Requirements:

  • Proven experience as a Machine Learning Engineer, with at least 4 years in industry or equivalent academic experience (thesis-based Master’s or PhD).
  • Strong proficiency in Python; write clean, efficient code with minimal handholding.
  • Demonstrated experience developing novel, custom machine learning models and embeddings: inventing new approaches rather than applying off-the-shelf LLM or image-processing tools.
  • Hands-on experience with large language models (LLMs).
  • Familiarity with a deep learning framework such as PyTorch, TensorFlow, or JAX.
  • Ability to work in a fast-paced startup environment and manage multiple tasks simultaneously.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and teamwork skills.

Bonus Skills:

  • Experience with ML platforms such as Amazon SageMaker, Azure ML, or Google Cloud AI Platform.
  • Experience with cloud platforms (e.g., AWS, Google Cloud).
  • Experience with backend development and frameworks (e.g., Django, Flask, SQL).
  • CAD, geometry, or computational geometry domain experience.

What We Offer:

  • Competitive salary and equity options.
  • Comprehensive health insurance, including medical, dental, and vision coverage.
  • Catered lunch.
  • Unlimited time-off.
  • A collaborative and inclusive work environment.
  • Opportunities for professional growth and development.
  • The chance to be part of a passionate team building innovative products.

Our application process consists of five steps:

  • Short Survey: After reviewing your resume, if you meet the minimum requirements, we will send you a short questionnaire via email**.** This should take no longer than 15 minutes.****

  • Initial Call: After successful review of the survey, we will conduct an initial call via Google Meet. It will help us get to know you better and discuss your background and interests. It will also give you an opportunity to learn more about our company culture and the role. The scheduling link will be provided in a future email.

  • Coding Challenge: If the initial call goes well, we will send you a coding challenge that should take no longer than 8 hours to complete. This challenge will help us assess your coding skills and problem-solving abilities in a practical context.

  • Interviews: Upon successful completion of the coding challenge, we will schedule a series of technical interviews, where you will meet our team including the CEO and CTO. We will invite you over to our office in San Mateo if you are based in the Bay Area. For candidates who reside outside of the Bay Area, we will do the interview via Google Meet. These interviews will further assess your technical skills and problem-solving abilities relevant to the position.

  • Offer: Upon successful completion of the technical interviews, we will discuss the terms of employment and extend a formal offer to you.

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