Sr AI/ML Engineer
$102.4kVizient
When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. Summary: In this role, you will design, build, and deploy scalable AI and machine learning solutions that drive business impact. You will lead the full AI lifecycle from experimentation through production, developing both traditional ML models and Large Language Model (LLM)-powered systems such as Retrieval-Augmented Generation (RAG) pipelines and agentic workflows. You will collaborate across teams to translate complex problems into reliable, high-performing solutions aligned with client needs. We are seeking engineers who are driven, curious, and energized by the pace of AI innovation, bringing emerging tools and techniques into practical, production-ready systems while taking ownership and helping shape the next generation of AI capabilities. Responsibilities: * Lead the design, development, and deployment of machine learning models and LLM-based applications. * Translate business challenges into scalable AI solutions and define success metrics aligned with business KPIs. * Design and implement RAG pipelines, embedding strategies, and vector search architectures. * Build agentic workflows, prompt strategies, and orchestration patterns for LLM systems. * Own AI/ML solutions end to end, from scoping and design through implementation, deployment, and operationalization, with a high degree of autonomy. * Evaluate model and LLM performance using automated and human-in-the-loop methods while implementing guardrails and monitoring.
- Optimize AI systems for latency, cost, scalability, and reliability.
- Architect and maintain scalable deployment strategies, CI/CD pipelines, and
- 5 or more years of relevant experience required.
- Experience in ML engineering, applied AI, or related fields preferred.
- Experience deploying machine learning models into production environments
- Experience with vector databases and embedding workflows required.
- Familiarity with orchestration frameworks such as LangChain, LlamaIndex, or
- Experience designing AI platforms or reusable AI templates preferred.
- Familiarity with model monitoring frameworks and evaluation tooling for LLM
- Experience working in regulated or high-compliance environments preferred.
- Experience optimizing cost and performance for large-scale inference
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