Senior SRE/ML Ops Engineer – Performance

About This Opportunity

We are representing a confidential streaming advertising technology company in Paris that is scaling rapidly. Our client operates a performance-driven platform serving millions of households, and they need a Senior SRE/ML Ops Engineer to own reliability and performance across their production bidding infrastructure.

This is a high-impact role on a small, focused team where your work directly affects advertiser outcomes and platform economics. You'll own the production serving path—prediction serving, bidding engine, pacing, and delivery—while partnering closely with data scientists shipping models into production.

Responsibilities

• Own reliability across the production stack: define SLOs, build observability systems, and shape on-call practices
• Optimize p99 latency on the serving path and reduce infrastructure costs without compromising performance
• Work on the data layer under real-time serving, particularly Redis access patterns, caching strategy, and degradation behavior
• Build end-to-end stress testing capabilities in staging to identify capacity limits before they hit production
• Handle capacity planning and infrastructure cost management as traffic volume grows
• Run incident response and ensure postmortems result in shipped improvements
• Collaborate with data scientists and platform engineers to support model deployments
• Partner with other engineering teams whose systems interact with the bidding stack

What We're Looking For

Required:

• Proven experience owning latency-sensitive services in production, including on-call responsibility
• Strong Kubernetes and cloud infrastructure fundamentals with debugging expertise for latency issues
• Deep observability experience: metrics, tracing, logs, and alert design
• Proficiency with infrastructure as code and CI/CD practices
• Ability to take ownership of existing systems you didn't design
• Paris-based strongly preferred; relocation and visa sponsorship available

Nice to Have:

• High-QPS, low-latency serving experience in ad tech, trading, gaming, or streaming
• Deep debugging experience with Redis, Kafka, or similar technologies
• Capacity planning and cost optimization on large-scale infrastructure
• Experience with model rollouts and their unique challenges
• Background in programmatic advertising, auctions, or connected TV
• Experience with Go, Rust, or Python

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screening to understand your background and ensure alignment with the role. If there's a strong match, we'll submit your profile to our client for consideration. Please do not contact the client directly—all communication flows through our talent team to ensure a smooth, professional process.

The client's interview process includes: recruiter screen (30 min), manager interview, technical debugging and systems design interview with the performance engineering team, calibration interview with senior leadership, and offer. Reference checks are conducted with discretion.

Pay

Compensation details will be discussed during the screening process based on your experience and the client's budget.

Equal Opportunity: Get A Job.ai is an equal opportunity employer. We evaluate all applicants without regard to race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.