Senior Machine Learning Engineer

What you'll do

• Build and optimize production-ready LLM agents using prompt engineering, retrieval, memory, and tool-calling capabilities.
• Develop scalable evaluation pipelines to measure accuracy, latency, cost efficiency, and hallucination rates.
• Integrate agentic workflows with vector databases, microservices, and internal APIs for reliable context retrieval.
• Fine-tune domain-specific LLMs using supervised fine-tuning, LoRA/PEFT, and preference optimization techniques.
• Productionize AI services by implementing security guardrails, observability, and robust deployment pipelines.
• Track production metrics to identify data drift and implement systematic retuning strategies for model performance.
• Prototype emerging AI technologies and scale early-stage concepts into enterprise-grade software.

What we're looking for

• Bachelor’s degree in a relevant field with 5+ years of related experience, an advanced degree with 3+ years of experience, or equivalent practical work experience.
• 5+ years of professional software/ML/AI engineering experience with demonstrated ownership of production systems.
• Proficiency in Python and experience with backend languages such as C#, Java, or TypeScript.
• Hands-on experience developing LLM applications, retrieval-augmented generation (RAG), agentic workflows, and multi-step reasoning.
• Proven track record building and operating AI/ML systems in production, including evaluation frameworks, monitoring, safety guardrails, and observability.
• Experience deploying and scaling cloud-native infrastructure, containers, and automated pipelines.
• Familiarity with Docker, Kubernetes, and MLOps practices (preferred).
• Authorization to work for any employer in the U.S.