Quick overview
SeniorityMid Senior
Work modeHybrid
LocationUnited States
AWSMLOpsDatabricksGoogle CloudHugging FaceLLMPythonGenerative AIAzureMachine LearningAgileCI/CDLangChainLangGraphRAG
Job description
We are seeking a Senior AI/ML Engineer to join a growing AI and machine learning team focused on developing next-generation predictive analytics, intelligent automation, and generative AI solutions. This role will partner closely with data scientists, software engineers, and business stakeholders to design, build, and deploy scalable AI systems that drive meaningful business outcomes.
As a Senior AI/ML Engineer, you will contribute to the development of cutting-edge machine learning and AI products that blend predictive modeling, optimization, and generative reasoning. You'll play a key role in building intelligent, scalable systems while helping shape best practices across machine learning engineering, MLOps, and modern AI architectures.
Required Skills & Experience
As a Senior AI/ML Engineer, you will contribute to the development of cutting-edge machine learning and AI products that blend predictive modeling, optimization, and generative reasoning. You'll play a key role in building intelligent, scalable systems while helping shape best practices across machine learning engineering, MLOps, and modern AI architectures.
Required Skills & Experience
- Master's degree in Computer Science, Software Engineering, Data Science, or a related field (PhD preferred)
- 7+ years of experience designing, developing, and deploying machine learning solutions in production environments
- Strong Python development experience, including building reusable packages, frameworks, and automation tools
- Hands-on experience with Databricks for large-scale data processing, analytics, and machine learning workflows
- Deep understanding of machine learning systems design, MLOps, model lifecycle management, and scalable inference systems
- Experience working in cloud environments such as Azure, AWS, or Google Cloud Platform
- Experience with containerization technologies, orchestration tools, and CI/CD pipelines
- Proficiency with distributed computing frameworks, machine learning libraries, and relational/non-relational databases
- Experience integrating generative AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, or AutoGen into enterprise solutions
- Strong problem-solving, communication, and collaboration skills
- Experience developing agentic AI systems, AI orchestration platforms, or AI-assisted decision-making workflows
- Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures
- Knowledge of evaluation, monitoring, and observability frameworks for AI and LLM applications
- Industry experience within utilities, energy, power, infrastructure, or other complex operational environments
- Deep expertise within the Databricks ecosystem for AI and data engineering solutions
- Collaborate with cross-functional teams to design, develop, and deploy scalable software products that incorporate machine learning and AI models
- Build reusable Python packages and scalable data pipelines to support ML and AI initiatives
- Design and implement AI systems utilizing LLMs, Retrieval-Augmented Generation (RAG), and agent-based workflows
- Develop evaluation, observability, and monitoring frameworks to assess model quality, reasoning, consistency, and fairness
- Optimize database performance and data-processing workflows for large-scale AI applications
- Break complex machine learning and AI initiatives into actionable technical requirements and development plans
- Ensure high-quality testing, code coverage, and peer review practices across AI engineering projects
- Contribute to MLOps, continuous delivery, and Agile software development processes
- Research and implement emerging AI technologies, frameworks, and best practices
- Partner with stakeholders to translate business challenges into production-ready AI solutions
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