Machine Learning Engineer
$110k - $165kAdvatix
Department : Information Technology, Type: Full Time Job Title: Machine Learning Engineer / Research Engineer Pay: $$110,000 – $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) – Onsite Preferred Schedule: Full time, Permanent Role Visa Sponsorship: Not Available Relocation Assistance: Not Available Role Summary We are looking for a highly skilled Machine Learning Engineer / Research Engineer to join our founding team and help develop intelligent systems that transform how hardware and mechanical engineers design products. This is a unique opportunity to work at the intersection of cutting‑edge machine learning research and real‑world engineering applications. You'll collaborate directly with founders, engineers, and customers to design, train, deploy, and continuously improve machine learning systems that accelerate CAD workflows and hardware design. As one of the earliest ML hires, you will have significant ownership over technical direction, architecture decisions, and the long‑term evolution of our AI platform. Key Responsibilities Machine Learning Research & Development Design, train, and optimize custom deep learning models that understand CAD workflows and generate intelligent next‑step design recommendations. Develop novel machine learning approaches for geometry, design, and engineering‑related datasets. Evaluate emerging research in areas such as sequence modeling, geometric deep learning, representation learning, and foundation models. Data & Model Infrastructure Build and maintain scalable Python‑based training, evaluation, and experimentation pipelines. Transform complex, real‑world CAD and geometry data into high‑quality training datasets and signals. Implement robust offline and online evaluation frameworks to measure model performance and business impact. Production ML Systems Own the complete ML lifecycle from research and prototyping through deployment, monitoring, and optimization. Architect model‑serving infrastructure and backend components that enable fast, reliable integration into CAD environments. Establish best practices for experimentation, logging, model versioning, and performance monitoring. Cross‑Functional Collaboration Work closely with founders, mechanical engineers, hardware engineers, and early customers to understand workflows and translate them into ML solutions. Collaborate with backend engineers on APIs, infrastructure, data models, and platform scalability. Help define the long‑term strategy for applying machine learning to hardware and CAD design. Skills & Qualifications Machine Learning Expertise 4+ years of hands‑on machine learning experience in industry, research, or a combination of both. Equivalent Master's or PhD research experience will be considered. Demonstrated success designing, training, improving, and deploying machine learning models—not simply utilizing hosted AI APIs. Deep Learning & Research Expert‑level proficiency with PyTorch (preferred) or similar frameworks such as TensorFlow or JAX. Experience implementing custom architectures, loss functions, optimization methods, and training loops. Strong understanding of model evaluation, experimentation, and performance trade‑offs. Software Engineering Strong Python programming skills with experience building production‑ready systems. Ability to write clean, maintainable, and well‑tested code with appropriate documentation and abstractions. Experience developing scalable ML infrastructure and backend services. Ownership & Execution Proven ability to independently drive projects from concept through deployment. Experience building end‑to‑end ML systems including data pipelines, experimentation frameworks, model training, deployment, and monitoring. Comfortable solving ambiguous, open‑ended technical problems. Communication & Collaboration Excellent communication skills with the ability to explain technical concepts to both technical and non‑technical stakeholders. Experience working cross‑functionally with engineers, product teams, researchers, and customers. Startup Mindset Thrives in fast‑paced, high‑ownership environments. Comfortable wearing multiple hats across machine learning, research, backend engineering, and infrastructure. Preferred Qualifications Published research papers or meaningful open‑source contributions demonstrating novel technical work. Experience with: CAD systems and workflows Computational geometry Computer graphics 3D representations Robotics Familiarity with cloud ML infrastructure (AWS, GCP). Experience with backend frameworks such as FastAPI, Flask, or Django. Must‑Have Requirements Must be based in the United States and possess valid work authorization. Strong proficiency in Python and modern deep learning frameworks (PyTorch preferred). Demonstrated experience building and deploying custom machine learning models from scratch. Experience designing architectures, creating training pipelines, and shipping ML features to production. Minimum 4 years of relevant industry or equivalent academic experience. Benefits & Perks Competitive salary ($110,000 – $175,000) Meaningful equity ownership Comprehensive medical, dental, and vision insurance Catered team lunches at the San Mateo office Unlimited/flexible paid time off High‑impact role within a YC‑backed startup Direct collaboration with experienced founders and engineers Significant opportunities for growth, learning, and career advancement Opportunity to help define the future of AI‑powered CAD and hardware design HRforGrowthis an extension of the Growth Catalyst Group (GCG), a partnership of companies with more than 65 years of operating experience and a history of successfully serving customers across industries and disciplines. GCG® is one of the world’s leading providers of business transformation solutions related to supply chain and technology solutions for order fulfillment and marketing execution. We are committed to an inclusive workplace that does not discriminate against race, nationality, religion, age, marital status, physical or mental disability, sexual orientation, gender, orgender identity. We believe in diversity and encourage anyqualifiedindividual to apply. We are an EEOCEmployer. #J-18808-Ljbffr
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