Senior Site Reliability Engineer

Overview

Job Description

Responsibilities

• - Own the Machine Learning Inference Infrastructure at Photoroom, powering millions of AI requests every day across GPU-based systems.
• - Responsible for the infrastructure that deploys and runs machine learning workloads, partnering closely with ML engineers to ensure services remain reliable, scalable and cost-efficient.
• - Design and build cloud-agnostic infrastructure solutions that support both current and future AI workloads.
• - Work across the full infrastructure lifecycle, from architecture and implementation through to monitoring, optimisation and incident management, using tools such as Datadog to maintain system health.
• - Build and improve systems for load balancing, autoscaling, queuing and workload orchestration, ensuring consistent performance under rapidly growing demand.
• - Work directly with engineers across ML, Product, Mobile and Web teams to identify bottlenecks, improve deployment workflows and enable faster iteration.
• - Monitor production systems, analyse usage patterns and make infrastructure decisions based on real-world performance and user impact.
• - Optional: Participate in the team’s on-call rotation to help maintain platform reliability.

Required Skills

• - Experience designing and operating large-scale distributed systems with high availability and reliability requirements.
• - Hands-on experience with load balancing, autoscaling, queuing systems and traffic management at scale.
• - Worked on low-latency, real-time backend systems and understand how to optimise for performance and throughput.
• - Experience building resilient, redundant infrastructure capable of handling failures gracefully.
• - Designed and operated platforms that deploy and run containerised workloads at high scale while maintaining an excellent developer experience.
• - Experience supporting workloads that vary significantly in duration, from milliseconds to several seconds.
• - Highly pragmatic and focus on delivering business impact quickly, leveraging existing tools and frameworks where appropriate rather than reinventing solutions.
• - Strong ownership and are comfortable making technical decisions independently while collaborating effectively across teams.
• - Previously worked in a high-growth startup or similarly fast-moving environment.
• - Enjoy learning from others, sharing knowledge and contributing to a collaborative engineering culture.
• - Experience supporting machine learning infrastructure or GPU workloads is a plus, but not required.
• - Fluent in English (French is not required).

Benefits

• - Work flexibly from one of our core countries: France, Germany, Italy, Spain, Poland, UK, Ireland or Portugal.
• - Regular team gatherings, including in-person onboarding in Paris (1–2 weeks), yearly company offsite and team retreat, quarterly in-person meetings (monthly during probation period), and social events such as winter parties and hackathons.
• - 30 days annual leave plus local public holidays.
• - Competitive equity package with stock options/BSPCE, giving you ownership in our growing company.
• - €1,000 one-time home office grant OR €400 per month co-working space stipend.
• - €1,000 annual learning and development budget for training, courses, books and professional development.
• - Private health insurance.
• - Access to personalised mental health support, including 1:1 sessions with therapists or coaches, self-care tools and wellbeing resources via MokaCare.
• - Sports and cultural activities reimbursement.
• - Relocation support (up to €10k) available for those choosing to move to France, including apartment-finding assistance and visa support.