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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Koch, Inc. - **Location:** Fremont, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $170,000 - $250,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Systems Engineering, Artificial Neural Networks, Microsoft Azure, CAD Data Exchange, Data Transmissions, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Azure Machine Learning, Data Logging, Graph Neural Networks, Boosted Trees, Pytorch, Surrogate Models, Large Language Models, Deep Learning, Gaussian, Machine Learning Operations, Azure AI, Model Registry - **Published:** November 10, 2026 - **Apply:** https://www.careerbuilder.com/job-details/machine-learning-engineer-fremont-ca--2c1a96c4-cfba-4453-98f1-080fffd05df2 ## About the Role Machine Learning, English Language, Facebook, LinkedIn, Physics, Simulation, Microsoft Windows Azure, Machine Learning, Candidate Screening, Data Science, * Extensive hands-on experience building, training, and deploying ML models in production - not just using pretrained APIs. * 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML). * Strong Python with PyTorch or TensorFlow. * Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain. * Experience with Azure Machine Learning or a similar cloud ML platform. * Familiarity with uncertainty quantification (Bayesian approaches, ensembling). What Will Put You Ahead * Direct experience with industry-standard EM or physics simulation tools. * Geometric deep learning (graph neural networks, mesh-based models) for CAD data. * Background in RF/high-speed electronics or interconnect design. ## Description * Employee Login * Home * Search Jobs * Life at Koch * Companies * Career Opportunities * How We Hire * Early Careers * Recruiting Events * Candidate Portal * Join our Talent Community * Employee Login * Learn More About Koch * Latest Koch News * English - US * Deutsch * English - US * Español - ES * Français - France * Polski, The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle. Our Team Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You''ll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast. What You Will Do * Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series). * Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit. * Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive. * Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis. * Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning., * Strictly Necessary Cookies Strictly Necessary Cookies Always Active Strictly Necessary Cookies These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. 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