> Markdown version of [/jobs/ext/736613-machine-learning-engineer-inference](https://www.wearedevelopers.com/jobs/ext/736613-machine-learning-engineer-inference). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Inference - **Company:** MindBeam LLC - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $150,000.0 - $190,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computer Programming, Programming Tools, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, AI Infrastructure, Pytorch, Kubernetes, Information Technology, Enterprise Integration, Machine Learning Operations, Docker - **Published:** June 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=22a044a87e7ca9ca ## About the Role Do you have experience in User-facing feature development?, * Bachelor's or advanced degree in Computer Science, Engineering, or related field-or equivalent experience. * 2+ years of experience building developer tools, APIs, or ML/AI applications. * Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX). * Familiarity with distributed systems, containers, and orchestration (Docker/Kubernetes). * Understanding of security, compliance, and enterprise integration best practices., You care deeply about usability and accessibility in AI. You thrive at simplifying complexity, and you're energized by building bridges between research and real-world adoption. ## Description * Develop user-facing APIs, SDKs, and tools that streamline access to Mindbeam's AI infrastructure. * Partner with research and product teams to translate complex ML workflows into clear, usable abstractions. * Optimize interfaces for scalability, security, and performance. * Advocate for the developer experience by gathering feedback and iterating rapidly. * Collaborate cross-functionally to ensure interfaces integrate seamlessly with enterprise environments. ## Related Videos - [You are not an AI developer](https://www.wearedevelopers.com/videos/1148-you-are-not-an-ai-developer) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [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) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) ## Related Articles - [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) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [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)