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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Support Engineer - **Company:** Source Inc. - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Bash Shell, C++ (Programming Language), Cloud Computing, Cloud Engineering, Encodings, High-Level Architecture, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Azure Machine Learning, Virtualization Technology, Graphics Processing Unit (GPU), Google Cloud, Pytorch, Large Language Models, Deep Learning, Generative AI, Containerization, Machine Learning Operations, Artificial Intelligence Markup Language (AIML), Data Pipelines, Golang - **Published:** July 31, 2026 - **Apply:** https://www.dice.com/job-detail/6109679c-b55b-40ce-8587-accac32466af ## About the Role Experience: Must have 10+ years of experience, Ideal candidates should possess a strong foundation in AIML, machine learning, and natural language processing, with a specific emphasis on data analysis, data pipelines, and model deployment. They should be capable of troubleshooting model-related issues, optimizing model performance, and providing expert support for various AIML platforms. Technical Skills: Compute Fundamentals: Demonstrates a deep understanding of compute concepts, including virtualization, containerization, operating systems, and system administration. Cloud Technologies: Experience with cloud platforms like Google Cloud Platform, AWS, and Azure, including their AI/ML services. Generative AI Experience with LLM and Generative AI and Google Cloud Products and services (e.g Vertex AI, Dialogflow, Gemini) ML Development: Experience with Machine Learning model development and deployment. AIML Frameworks: Experience with frameworks for deep learning (e.g. PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g. TPUs, GPUs), model architectures (e.g. encoders, decoders, transformers), and using machine learning APIs. Experience: Troubleshooting Code Experience: 2 years of experience reading code in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.) or in system design. AIML Experience: +2 Experience with Machine Learning model development and deployment. Troubleshooting Experience: 3+ years of experience in troubleshooting, diagnosing, and resolving complex issues. Support Experience: Familiarity with support methodologies, case lifecycles, and analytical skills for breaking down issues. Certifications Google Machine Learning Engineer certification is desired. * + Google Cloud Associate Cloud Engineer (ACE) certification is required. ## Related Videos - [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) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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