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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Cognex Corporation - **Location:** Natick, MA, United States - **Experience:** Expert - **Salary:** $115,000.0 - $225,000.0 - **Contract:** Permanent contract - **Skills:** Testing (Software), Training Data, C (Programming Language), Artificial Intelligence, Artificial Neural Networks, Computer Vision, Automation of Tests, C++ (Programming Language), Configuration Management, Program Optimization, Computer Programming, Continuous Delivery, Continuous Integration, Software Debugging, Embedded Software, Design of User Interfaces, Hardware Design, Human-Computer Interaction, Issue Tracking Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Signal Processing, Software Engineering, Speech Recognition, Scripting, Pytorch, Deep Learning, Information Technology, Low Latency, Machine Learning Operations, Multiplatform, Software Version Control - **Published:** August 9, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-machine-learning-engineer-natick-ma--15c1fea6-c4b4-4477-b60d-f385012d122e ## About the Role * Industry or academic experience developing and optimizing deep learning algorithms in one or more relevant technical areas - computer vision, natural language processing, speech recognition. * Deep understanding of AI concepts including training strategies, loss functions, evaluation metrics, and ML operations. * Strong Python programming skills. * Proficient C/C++ experience for performance-critical systems. * Proficiency with ML frameworks (PyTorch, TensorFlow), model optimization, and ML development lifecycles. * Strong debugging and analytical problem-solving skills. * Experience with software development practices including version control, CI/CD, and issue tracking. * Excellent communication and collaboration skills. Desired * Background in computer vision, signal processing, or related fields. * Experience with embedded ML, quantization, or hardware-aware optimization. * Hands-on experience building and deploying efficient deep learning models for real-world computer vision applications. Minimum Education & Experience * Bachelors or Masters degree in Computer Science, Computer/Electrical Engineering, Mathematics or related field, and 5+ years of relevant experience in AI/ML, software engineering, or applied research roles., Algorithms, Analysis Skills, Artificial Intelligence (AI), Benchmarking, C Programming Language, C++ Programming Language, Communication Skills, Computer Programming, Computer Science, Computer Vision, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Debugging Skills, Deep Learning, Electrical Engineering, Embedded Hardware, Embedded Software, Embedded Systems, Hardware Design, Identify Issues, Image Editors, Incentive Programs, Low Power, Machine Learning, Mathematics, Mentoring, Metrics, Multiplatform/Cross-Platform, Natural Language Processing (NLP), Neural Networks, Problem Solving Skills, Product Lifecycle, Prototyping, Python Programming/Scripting Language, Research & Development (R&D), Research Skills, Sales, Signal Processing, Software Development, Software Engineering, Software Testing, Source Code/Configuration Management (SCM), Speech Recognition, Team Player, Technical Leadership, Test Plan/Schedule, Training Data Sets, User Interface/Experience (UI/UX) ## Description * Research, design, and implement efficient deep learning models for industrial machine vision tasks, with a focus on algorithms with low power, low latency and data efficiency requirements. * Collaborate with cross functional engineers to transition experimental AI models into production-ready components for embedded systems. * Develop high-performance Python and C/C++ code for training, optimization, benchmarking, and deployment. * Lead model-architecture discussions and make long-term technical decisions across platforms. * Optimize neural networks for resource-constrained environments (quantization, pruning, distillation, hardware-aware design). * Build evaluation pipelines, datasets, and tools to assess model accuracy, robustness, runtime performance, and reliability. * Diagnose and resolve complex issues across hardware, software, and ML components. * Provide technical guidance to engineers developing UIs, test frameworks, and runtime components. * Mentor junior engineers and champion engineering excellence in ML research and development. ## Related Videos - [Machine Learning for Software Developers (and Knitters)](https://www.wearedevelopers.com/videos/154-machine-learning-for-software-developers-and-knitters) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [JavaScript? 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