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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI / ML Engineer - **Company:** E Source - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $115,000.0 - $145,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Code Coverage, Computer Programming, Databases, Continuous Delivery, Information Engineering, Database Design, Distributed Computing Environment, Text Processing, Python (Programming Language), Machine Learning, Software Engineering, Data Processing, Large Language Models, Multi-Agent Systems, Reliability of Systems, Generative AI, Containerization, Information Technology, HuggingFace, Machine Learning Operations, Databricks - **Published:** June 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ea91413547821117 ## About the Role Do you have experience in Working in the energy & utilities sector?, Do you have a Master's degree?, * Master's degree in computer science, software engineering, data science, or a related field (PhD preferred). * Minimum of 7 years of professional experience designing, developing, and deploying machine learning software products independently and collaboratively. * Strong programming skills in Python, with experience developing reusable packages and automation tools. * Familiarity with Databricks for scalable data processing and collaborative analytics. * Solid understanding of machine learning systems design concepts, including model lifecycle management, MLOps, and scalable inference. * Hands-on experience with cloud infrastructure (Azure, AWS, or GCP), containerization, and CI/CD pipelines. * Proficiency with distributed computing frameworks, machine learning packages, and both relational and nonrelational databases. * Familiarity with generative AI tools and frameworks (e.g., AutoGen, Hugging Face, LangChain, LangGraph, LlamaIndex) and their integration into enterprise pipelines. * Experience developing or evaluating agentic AI systems, AI orchestration, or AI-assisted decision-making workflows is an asset. * Excellent problem-solving and analytical skills, with the ability to break down complex tasks into actionable steps. * Strong communication and collaboration skills, with a track record of working effectively in cross-functional teams. * Knowledge or experience in the utility, power, or energy sectors is a plus. * Deep knowledge in Databricks tech stack for AI and data engineering is a plus.ยท, Applicants must be authorized to work for any employer in the US or Canada. We're unable to sponsor or take over sponsorship of employment visas or Labour Market Impact Assessments (Cdn) at this time. ## Description Joining E Source as a Senior AI/ML Engineer is an exciting opportunity to work with a dynamic and talented team, leveraging your skills to drive meaningful impact in the utility industry. You'll contribute to the next generation of AI and ML solutions that blend predictive modeling, optimization, and generative reasoning to empower sustainable decisions. If you are a self-motivated engineer who thrives in a collaborative, innovative environment, and if you're passionate about building intelligent, scalable AI/ML systems, we invite you to apply and help shape the future of utilities. As a Senior AI/ML Engineer at E Source, you'll play a crucial role in our machine learning engineering team. Collaborating with data scientists and software engineers, you'll contribute to the development of cutting-edge ML and AI products that support our mission of building a sustainable future with utilities. Your expertise will be instrumental in building tools and pipelines for developing and scaling machine-learning models, including emerging AI system design components and agentic architectures. You'll work across a range of use cases-like electrification, network reliability, geospatial analysis, time series forecasting, image and text processing, and AI-driven decision systems-using both traditional ML and modern generative AI approaches. In this role, you will: * Collaborate with cross-functional teams to design, develop, and deploy scalable software products that incorporate machine learning and AI models. * Build reusable Python packages to support the implementation of ML/AI algorithms and data-processing pipelines. * Contribute to the design of AI systems, including components for retrieval-augmented generation (RAG), LLM integration, and agent-based workflows. * Develop agentic evaluation and monitoring frameworks to assess model reasoning, consistency, and fairness. * Evaluate database design and create optimized performance queries for efficient data processing and retrieval. * Break down complex MLE and AI tasks into manageable user and technical stories, ensuring efficient and effective implementation. * Ensure high-quality test coverage of ML code and participate in peer reviews to provide valuable recommendations. * Stay updated on the latest advances in machine learning engineering, generative AI, and AI system orchestration, and incorporate relevant practices into our workflows. * Contribute to continuous delivery and Agile development processes, adhering to best practices in ML and AI engineering. ## Related Videos - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Got AI ideas but no money? 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