1 month ago
Chicago, IL, USA +2 moreSenior
Base Salary
$102k - $179k/yr
Responsibilities
- Design, develop, deploy, and own machine learning models and LLM-based applications end to end.
- Design RAG pipelines, embedding strategies, vector search architectures, agentic workflows, prompt strategies, and LLM orchestration patterns.
- Evaluate predictive ML and LLM performance using automated and human-in-the-loop methods, with guardrails and monitoring.
- Optimize AI systems for latency, cost, scalability, and reliability.
- Architect and maintain deployment strategies, CI/CD pipelines, MLOps workflows, monitoring, drift detection, retraining pipelines, and model lifecycle management.
- Design and maintain production-grade data pipelines with validation, lineage, and reproducibility.
- Translate business challenges into scalable AI solutions and define success metrics aligned with business KPIs.
- Mentor team members, influence AI architecture decisions, and promote responsible AI governance.
- Stay current with AI/ML advancements and incorporate relevant innovations into production solutions.
Requirements
- A relevant degree is preferred; an advanced degree in Computer Science, Engineering, Data Science, or a related field is a plus.
- At least 5 years of relevant experience is required.
- Experience in ML engineering, applied AI, or related fields is preferred.
- Production deployment experience for machine learning models is required.
- Experience building and deploying LLM-powered applications, including RAG systems and agentic workflows, is required.
- Strong Python expertise and production-grade software engineering practices are required.
- Experience with model serving frameworks and API development, such as FastAPI and MLflow, is required.
- Experience with vector databases and embedding workflows is required.
- Familiarity with orchestration frameworks such as LangChain or LlamaIndex is required.
- Experience with CI/CD pipelines, containerization, and cloud-based deployment environments is required.
- Strong understanding of evaluation methodologies for predictive ML and LLM systems is required.
- Experience in startup, high-growth, or large-scale enterprise AI/ML environments is preferred.
- Experience designing AI platforms or reusable AI templates is preferred.
- Familiarity with model monitoring frameworks and LLM evaluation tooling is preferred.
- Experience in regulated or high-compliance environments, large-scale inference optimization, and foundation-model fine-tuning or adaptation is preferred.
Benefits
- Comprehensive benefits plan.
- Incentive eligible.
- Salary range of $102,400.00 to $179,000.00, adjusted as applicable for geographic factors and individual circumstances.
Tech Stack
Categories
