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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer (MLE) - **Company:** Maxinsights Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Experienced - **Salary:** $160,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Computer Vision, Software Quality, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Tensorflow, Pytorch, Deep Learning, Information Technology, Free and Open-Source Software, Machine Learning Operations - **Published:** June 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4b15a880eea53d40 ## About the Role Do you have experience in System development?, Do you have a Bachelor's degree?, * Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience. * 3+ years of experience building and shipping machine learning systems. * Strong proficiency in Python and experience with at least one major deep learning framework (e.g., PyTorch, TensorFlow). * Solid understanding of modern deep learning concepts, training workflows, model * evaluation, and experience working with real-world, production-oriented ML pipelines. * Strong problem-solving skills and ability to work effectively in a fast-moving, collaborative environment., * PhD in a relevant field with a research focus in robot learning, embodied AI, or visual perception. * Experience with end-to-end ML systems, including data collection, training, inference, and deployment. * Background in computer vision, perception, or multi-modal machine learning, including egocentric or human-centric perception. * Familiarity with large-scale training, experimentation infrastructure, or production ML systems. * Ability and interest in learning new problem domains, data modalities, and ML techniques quickly. * Publications in leading venues, open-source contributions, or demonstrated impact in applied ML or AI systems. ## Description We are looking for a Machine Learning Engineer to join our core team building scalable ML systems for real-world perception and embodied intelligence. In this role, you will work on end-to-end machine learning systems, spanning data collection, model training, evaluation, and deployment. You will collaborate closely with researchers, engineers, and product teams to turn complex real-world data into robust, production-ready ML solutions. This role is well-suited for engineers who enjoy working across the ML stack, are comfortable operating in ambiguous problem spaces, and are excited about applying modern deep learning methods to real-world perception, human-centric, and embodied AI problems. Responsibilities * Design, build, and own end-to-end machine learning systems, from data exploration and model development to evaluation and deployment on large-scale, real-world data. * Apply state-of-the-art ML techniques to new problem domains and optimize models and pipelines for performance, efficiency, and reliability in production environments. * Drive measurable improvements in model performance, system robustness, and product capabilities through applied machine learning. * Collaborate closely with cross-functional teams to translate research ideas and product requirements into scalable ML solutions. * Contribute to technical design, code quality, and best practices, and help shape the long- term direction of the company's machine learning platform. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [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) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)