Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

Solution Development & Delivery

Implement AI-powered services and application features that integrate enterprise data and systems with LLMs and ML models.
Contribute to solution design by proposing approaches, identifying dependencies, and documenting tradeoffs and implementation plans.
Deliver features using strong engineering practices: test automation, code review, CI/CD, and operational readiness.

GenAI Engineering Practices

Build and tune RAG pipelines (retrieval, ranking, grounding) and implement prompt patterns that improve reliability and user experience.
Contribute to evaluation suites and regression testing to ensure quality and safety over time.
Implement guardrails and security controls (input/output validation, policy filtering, and data protection patterns) under guidance from senior engineers.

Reliability, Observability & Support

Instrument services with metrics, traces, logs, and dashboards;
Participate in incident response and post-incident improvements.
Support performance and cost optimization efforts (latency, throughput, caching, and model selection).

Collaboration & Continuous Improvement

Work closely with product, design, security, and platform teams to refine requirements and deliver customer-focused outcomes.
Mentor engineers at earlier career stages and share practical learnings with the broader AI/ML community of practice.
Stay current on GenAI and ML platform trends; propose incremental improvements that raise quality and accelerate delivery.