tem - Senior Staff MLOps Engineer

• Scaled an ML platform from early-stage: Demonstrable experience taking an ML platform from early stages to best-in-class infrastructure at a fast-moving company. You've been there, done it, and you're comfortable with the messiness and ambiguity that comes with scale-up life. • ML pipeline expertise: Deep experience across the whole MLOps lifecycle with ML pipeline orchestration (Metaflow, Prefect, Airflow or equivalent) and ML infrastructure (Sagemaker, Vertex AI, Chalk, or equivalent). • Model lifecycle tooling: Hands-on experience building or operating experiment tracking systems (MLflow, W&B, or similar), model registries, and governance tooling for model fleets at scale. Knows what good looks like and what to avoid. • Broad MLOps tooling knowledge: Across the ecosystem monitoring, drift detection, CI/CD for ML, containerisation, IaC (Terraform, AWS CDK). Able to evaluate trade-offs and make principled choices for a specific context, not just default to what they know. • Technical leadership track record: Evidence of setting platform direction, influencing cross-functional teams, and defining standards at Staff+ level. Raises the quality bar through design reviews, code reviews, and mentoring. Knows when to drive strategy and when to get into the weeds. • Heterogeneous workload experience: Experience designing and operating platforms serving heterogeneous workloads (e.g. forecasting, classification, operations research, etc), not just one model type across batch and real time applications. • Python, AWS + IaC: Strong Python; hands-on experience with AWS and infrastructure-as-code (Terraform, AWS CDK). • Worked in a role where ML is at the core of the product • Familiarity with Metaflow specifically • Experience with operations research, large-scale optimisation in a production context • Experience working with business critical time series forecasting models • Exposure to reinforcement learning in a production setting • Exposure to production LLM workloads e.g. fine tuning • 🗣️ Interview Process: • Our processes normally take around 2-3 weeks from first call to offer - please let us know about any adjustments to timelines that may be required. • 1. First call with our Talent Team (30 mins). This is to understand your experience, motivations, and discuss the role in more detail. • 2. Behaviour Interview with Tim, Head of Data (60 mins). This is your chance to really understand the role, the expectations, and ensure alignment on ways of working. • 3. Technical Interview with the Team (90 mins). You'll meet with potential peers in this session and work through a live technical exercise. • 4. Culture-Add Interview with Stakeholders (45 mins). The final session will be with two cross-functional stakeholders, and will explore how your values align with ours, and is designed to be a genuine two-way conversation, your chance to understand what it's really like to work at tem.