Lead Machine Learning Engineer

At TBAuctions, we are building the intelligent auction platform behind our brands, with machine learning and AI at its core: powering recommendations, search and personalization, valuation, supply-demand matching and streamlining processes with AI agents across millions of auctions.

We are looking for a Lead Machine Learning Engineer to head up our ML & AI team and the platform behind it, in a role that is equal parts hands-on and leadership. The ideal candidate has led and delivered large-scale ML/AI projects to production with real business impact, shaped technical direction, and built strong teams.

What you will do

Build and architect

• Own the architecture of our ML & AI systems end to end: data pipelines, feature and model stores, training and serving infrastructure, built as reusable capabilities our auction brands can share.

• Design the architecture and orchestration of our AI agents platform, with strong evaluation, monitoring and guardrails for reliable behaviour in production.

• Strengthen and contribute to our existing MLOps setup: automated training, validation, deployment and monitoring, experiment tracking and CI/CD.

• Design and build our recommendation, search and ranking systems end to end: candidate generation and retrieval, ranking models, embeddings and vector search, and real-time personalization at scale.

• Deploy models as robust APIs and scalable microservices, containerized and orchestrated with Kubernetes.

• Design systems, write and review code in a modern stack, and raise the bar on engineering best practices.

Lead and set direction

• Identify and prioritize the highest-impact opportunities across our auction brands and landscape, set and own the ML & AI roadmap.

• Frame business problems as ML tasks, define most impactful business metrics, and run rigorous experiments (A/B tests) to measure real impact.

• Drive continuous, incremental improvement of our ML & AI products, balancing near-term delivery with longer-term investment in the platform and innovation.

• Work closely with product managers and other tech leads to align priorities and delivery across teams.

• Manage business stakeholders and align them on priorities, scope and trade-offs, translating complex technical concepts to non-technical audiences effectively.

• Lead, mentor, hire and grow a team of ML engineers, supporting their career development and upskilling, and ensure chapter growth.

What you bring

• 7+ years in ML engineering, including 2 years leading technical direction of teams (formal people management is a plus).