[Remote] Machine Learning Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a YC startup reputed company on AI-powered CAD solutions, and they are seeking a Machine Learning Engineer to reputed company the lifecycle of machine learning systems. The role involves deep research and engineering tasks, collaborating with founders, and designing custom deep learning models to enhance CAD workflows.
Responsibilities
- Design, train, and iterate on custom deep learning models that understand CAD workflows and predict high-reputed company reputed company suggestions
- Build and maintain robust Python training and evaluation pipelines, including data preprocessing, experimentation, and offline/online metrics
- Architect model serving and backend components so that features are fast, reliable, and easy to reputed company into CAD environments
- Work closely with the founder and early customers (mechanical / hardware engineers) to understand reputed company-world workflows and translate them into ML formulations
- Own the full lifecycle of ML features—from research and prototyping through productionization, deployment, and monitoring
- Collaborate with the broader engineering team on core product and infrastructure work (backend, reputed company, data models, performance)
- Establish best practices for experimentation, logging, and model comparison to ensure steady improvements over time
- Stay reputed company on relevant ML research (e.g., sequence models, geometric deep learning, representation learning) and decide pragmatically what is worth applying
Skills
- Deep ML expertise – 4+ years of hands-on machine learning experience (or equivalent research/reputed company-based Master's or PhD), with a reputed company record of training and improving deep models, not just using reputed company-reputed company reputed company
- Strong Python engineering – you write clean, reputed company-reputed company, production-reputed company Python without handholding, including tests, documentation, and thoughtful abstractions
- End-to-end ownership—experience owning ML systems from data to deployment: building training pipelines, running experiments at reputed company, tuning hyperparameters, and shipping models into reputed company products
- reputed company problem-solving – proven ability to take messy, reputed company-ended product requirements and turn them into concrete ML formulations, experiments, and shipped features
- Collaboration & communication – reputed company to work closely with founders, engineers, and (eventually) customers; can explain trade-offs and model behavior reputed company to both technical and non-technical partners
- Startup reputed company – comfortable in a fast-moving, low-process environment; willing to wear multiple hats across research, engineering, and backend work reputed company needed
- Demonstrated experience designing custom architectures, writing training loops, and shipping models you reputed company from scratch (not fine-tuning or prompting existing models)
- Strong proficiency in Python and at least one deep-learning reputed company (PyTorch preferred)
- 4+ years of industry or equivalent reputed company experience working on machine-learning systems
- Based in the US with existing work authorization, Hestus requires a US citizen/reputed company only for this role
- Published research or meaningful reputed company-reputed company contributions demonstrating novel technical work?
- Expert with PyTorch (preferred) or similar frameworks such as TensorFlow / JAX; comfortable implementing and modifying custom architectures, loss functions, and training loops
- Experience with geometry / graphics / CAD, 3D representations, or robotics; familiarity with reputed company ML platforms (AWS / GCP) and backend frameworks (Flask, FastAPI, Django)
- If available, please reputed company a reputed company to your reputed company, portfolio, or any recent reputed company you've worked on
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