Operating, hardening, and continuously improving the production infrastructure that powers the Peakon Agent, AI Features, and related ML workloads
Managing the entire deployment lifecycle for the Peakon Agent and other AI Features
Contributing to driving operational excellence across the ML platform
Building and maintaining tooling to surface evaluation data
Supporting performance testing and load simulations
Collaborating on the automation of essential security upgrades for ML dependencies

Minimum 8 years of relevant industry experience
Holds a Bachelor’s/Master or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or equivalent practical experience
Proven track record as an MLOps or ML-savvy SRE/Platform Engineer supporting production-grade LLM and agentic systems
Proficient in Python and frameworks like LangChain and LlamaIndex
Hands-on experience operating containerized services (Docker, Kubernetes) using Git-based workflows (GitOps, GitHub Actions)
Solid understanding of modern ML stacks (platforms, feature stores, registries, messaging layers) or deep platform engineering background
Demonstrated ability to own production infrastructure end-to-end—managing monitoring, incident response, rollbacks, and continuous reliability/uptime improvements
Deep understanding of the model development lifecycle, specifically regarding model monitoring, regression tracking, and automated evaluation using tools like LangSmith
Strong communication and collaboration skills under pressure, acting as a bridge between ML engineers, backend teams, and central platform/security specialists.

Senior Machine Learning/AI Engineer, ML Ops Engineer

Key skills