TL;DR
Lead Site Reliability Engineer, ML Platform (AI): Own the reliability strategy and architectural evolution of hirify.global’s ML Deployment platform ensuring every machine learning model is served with stability and performance. Focus on scaling inference infrastructure to meet growing ML/AI demands.
Location: Vilnius or Kaunas
Salary: € 6,767- € 9,150 gross per month
Company
hirify.global is Europe’s leading platform for second-hand fashion with a growing range of categories.
What you will do
- Lead the technical roadmap for ML Deployment, ensuring our inference infrastructure scales to meet hirify.global’s growing ML/AI demands.
- Architect high-performance inference solutions, focusing on low-latency delivery and efficient GPU utilisation across our clusters.
- Define and drive reliability standards, including SLOs, error budgets, and sophisticated observability for model-serving systems.
- Mentor and grow senior engineers within the team, fostering a culture of technical excellence, pragmatism, and continuous learning.
- Oversee the integration of deployment workflows with automated experimentation patterns, such as A/B testing and shadow deployments.
Requirements
- Have a track record of leading technical problem-solving for complex, domain-level systems.
- Deeply experienced with Kubernetes, Linux internals, and high-scale networking.
- Strong programming background in Go or Python.
- Excellent written and spoken English, with the ability to articulate technical risks to both technical and non-technical stakeholders.
Nice to have
- Experience with GPU workloads and inference frameworks like KServe, vLLM, or NVIDIA Triton.
- Knowledge of LLM evaluation and observability tools (e.g. Langfuse).
Culture & Benefits
- Opportunity to benefit from share options programme.
- 25 working days of holiday.
- Home office support: IT workstation equipment and a personal budget of up to €540 for home workplace furniture.
- Hybrid workplace model where 2 days in the office are recommended but not enforced.
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