ml engineer in operational automation

The company is a high-growth investment and transformation firm that acquires established businesses and modernises them through advanced AI integration, turning legacy operational complexity into high-margin product value.

• Build and deploy end-to-end AI systems, including LLMs, agents, and RAG, to automate complex operational workflows;
• Partner with internal teams to convert messy legacy data into production-grade automation that increases throughput and reduces costs;
• Balance frontier AI capabilities with speed, simplicity, latency, cost, and reliability requirements;
• Work across the full stack using Python to ship scalable, AI-powered solutions.

• Deep experience in production AI design, including agentic workflows, model evaluation, and structured outputs;
• Strong track record of shipping software that delivered tangible business or operational outcomes;
• Expert Python skills;
• Ability to balance technical depth with pragmatic trade-offs involving accuracy, cost, and user experience;
• Nice to have: Go, TypeScript, modern vector/ML infrastructure.

• 4-Stage interview process focused on technical ability, product intuition, and team alignment.