Senior Software Engineer (MLOps) – Serving Careers at Datadog - Paris, France | Apply Now!
Datadog
Senior Software Engineer (MLOps) – Serving Careers at Datadog - Paris, France | Apply Now!
Job Description
Role Overview
Join Datadog's AI Platform team as a Senior Software Engineer (MLOps) – Serving in Paris or Sophia Antipolis, France. We're building the infrastructure that powers ML and LLM features across our industry-leading observability and security products. The Serving team ensures trained models deploy reliably at massive scale across multiple data centers and compute environments.
Our mission: enable self-serve, performant, observable model inference workflows. This includes Ray-based serving infrastructure, CPU/GPU inference endpoints, rollback strategies, shadow traffic, A/B testing, and continuous model improvement. Work across infrastructure, observability, and ML engineering to deliver production-ready capabilities used by Datadog's applied scientists and product teams.
Datadog operates a hybrid workplace prioritizing office culture for collaboration, creativity, and relationships while supporting work-life harmony.
Key Responsibilities at Datadog
- Architect and build systems for serving ML/LLM models across all data centers with strong SLAs, observability, and reliability
- Design and optimize Ray-based inference infrastructure handling both low- and high-throughput workloads
- Enable applied scientists to deploy/test models via self-service tools, CI/CD pipelines, and rollback mechanisms
- Implement A/B testing and shadow deployment capabilities for production model evaluation
- Collaborate with platform teams to improve GPU provisioning, traffic routing, and runtime performance
- Instrument inference workflows with rich telemetry (latency, token counts, errors) for performance/safety analysis
- Drive production readiness for inference endpoints across CPU and GPU environments
- Ensure scalability and reliability for Datadog's mission-critical AI platform components
- Partner cross-functionally with observability and security product teams
Qualifications & Requirements
Datadog seeks engineers passionate about AI infrastructure. You need:
- 6+ years backend/infrastructure engineering, including 2+ years ML/AI platforms
- Experience building distributed systems (model serving, realtime inference, large-scale APIs)
- Proficiency in Python, Go, or systems languages + performance tuning expertise
- Familiarity with Ray, TorchServe, Triton, BentoML or similar frameworks
- Hands-on GPU experience and heterogeneous compute infrastructure
- Bonus: AI observability, rollback strategies, deployment proxies
We value growth mindset. Don't meet every requirement? Apply anyway – passion for technology matters most at Datadog.
Salary & Benefits
Competitive Senior MLOps Engineer salary €85,000-€120,000 base (Paris/Sophia Antipolis market rates) + equity. Full package includes:
- New hire RSUs + ESPP stock programs
- Global health insurance covering family
- Free mental health benefits (employees + dependents 6+)
- Professional development + product training
- Mentor/buddy programs + Community Guilds
- Inclusion Talks + internal networking
- Hybrid work + commuter/fitness benefits
Benefits vary by location/employment type. France employees receive locally competitive perks.
Why Join Datadog?
Datadog (NASDAQ: DDOG) delivers growth + profitability in cloud observability. We break down silos, solve cloud complexity, and power digital transformation for customers worldwide. Built by engineers for engineers, used by organizations across industries.
Our people-first culture champions professional development, diversity, innovation, and work excellence. Join a collaborative, pragmatic community solving tough problems, taking smart risks, celebrating success. Experience #DatadogLife via Instagram, LinkedIn, Learning Center.
Work on cutting-edge AI/ML infrastructure powering observability products used by Fortune 500 companies. Hybrid Paris/Sophia Antipolis locations offer tech hub access + quality of life.
How to Apply
Ready to build the future of AI serving at Datadog? Apply now for Senior Software Engineer (MLOps) – Serving. Submit resume highlighting ML infrastructure experience. We'll review applications quickly – top candidates interview within 1 week.
Datadog provides equal opportunity. We celebrate diversity and encourage applications from all backgrounds. Let's build scalable AI together.
Locations
- Paris, France
- Sophia Antipolis, France
Salary
89,250 - 132,000 EUR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- MLOps Engineeringintermediate
- Ray Serving Frameworkintermediate
- Distributed Systemsintermediate
- Python Developmentintermediate
- Go Programmingintermediate
- GPU Optimizationintermediate
- Cloud Observabilityintermediate
- Model Inferenceintermediate
- CI/CD Pipelinesintermediate
- A/B Testingintermediate
- Telemetry Instrumentationintermediate
- Kubernetes Orchestrationintermediate
- Datadog Monitoringintermediate
- LLM Deploymentintermediate
- High-Throughput APIsintermediate
Required Qualifications
- 6+ years of backend or infrastructure engineering experience with 2+ years in ML/AI platforms (experience)
- Proven experience building distributed systems for model serving, realtime inference, or large-scale APIs (experience)
- Proficiency in Python, Go, or systems languages with performance tuning expertise in high-throughput environments (experience)
- Familiarity with Ray, TorchServe, Triton, or BentoML inference-serving frameworks (experience)
- Hands-on experience with GPUs and heterogeneous compute workloads (experience)
- Strong understanding of observability, rollback strategies, and production deployment best practices (experience)
Responsibilities
- Architect high-scale ML and LLM model serving systems across multiple data centers with strong SLAs
- Design and optimize Ray-based inference infrastructure for low- and high-throughput workloads
- Build self-service tools, CI/CD pipelines, and rollback mechanisms for applied scientists
- Implement A/B testing, shadow deployments, and continuous model improvement capabilities
- Collaborate with platform teams on GPU provisioning, traffic routing, and runtime optimization
- Instrument inference workflows with comprehensive telemetry including latency, token counts, and errors
- Ensure production-ready inference endpoints on CPU and GPU environments
- Drive observability and reliability for mission-critical AI platform components
- Enable cross-team model deployment workflows across Datadog's observability products
Benefits
- general: New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
- general: Comprehensive global health insurance for employees and dependents
- general: Free mental health benefits for employees and dependents age 6+
- general: Continuous professional development and product training programs
- general: Intradepartmental mentor and buddy programs for networking
- general: Inclusive company culture with Community Guilds (employee resource groups)
- general: Access to Inclusion Talks and internal panel discussions
- general: Competitive commuter benefits and fitness reimbursements
- general: Hybrid workplace with work-life harmony flexibility
Tags & Categories
Answer 10 quick questions to check your fit for Senior Software Engineer (MLOps) – Serving Careers at Datadog - Paris, France | Apply Now! @ Datadog.
Related Books and Jobs
Senior Software Engineer (MLOps) – Serving Careers at Datadog - Paris, France | Apply Now!
Datadog
Senior Software Engineer (MLOps) – Serving Careers at Datadog - Paris, France | Apply Now!
Job Description
Role Overview
Join Datadog's AI Platform team as a Senior Software Engineer (MLOps) – Serving in Paris or Sophia Antipolis, France. We're building the infrastructure that powers ML and LLM features across our industry-leading observability and security products. The Serving team ensures trained models deploy reliably at massive scale across multiple data centers and compute environments.
Our mission: enable self-serve, performant, observable model inference workflows. This includes Ray-based serving infrastructure, CPU/GPU inference endpoints, rollback strategies, shadow traffic, A/B testing, and continuous model improvement. Work across infrastructure, observability, and ML engineering to deliver production-ready capabilities used by Datadog's applied scientists and product teams.
Datadog operates a hybrid workplace prioritizing office culture for collaboration, creativity, and relationships while supporting work-life harmony.
Key Responsibilities at Datadog
- Architect and build systems for serving ML/LLM models across all data centers with strong SLAs, observability, and reliability
- Design and optimize Ray-based inference infrastructure handling both low- and high-throughput workloads
- Enable applied scientists to deploy/test models via self-service tools, CI/CD pipelines, and rollback mechanisms
- Implement A/B testing and shadow deployment capabilities for production model evaluation
- Collaborate with platform teams to improve GPU provisioning, traffic routing, and runtime performance
- Instrument inference workflows with rich telemetry (latency, token counts, errors) for performance/safety analysis
- Drive production readiness for inference endpoints across CPU and GPU environments
- Ensure scalability and reliability for Datadog's mission-critical AI platform components
- Partner cross-functionally with observability and security product teams
Qualifications & Requirements
Datadog seeks engineers passionate about AI infrastructure. You need:
- 6+ years backend/infrastructure engineering, including 2+ years ML/AI platforms
- Experience building distributed systems (model serving, realtime inference, large-scale APIs)
- Proficiency in Python, Go, or systems languages + performance tuning expertise
- Familiarity with Ray, TorchServe, Triton, BentoML or similar frameworks
- Hands-on GPU experience and heterogeneous compute infrastructure
- Bonus: AI observability, rollback strategies, deployment proxies
We value growth mindset. Don't meet every requirement? Apply anyway – passion for technology matters most at Datadog.
Salary & Benefits
Competitive Senior MLOps Engineer salary €85,000-€120,000 base (Paris/Sophia Antipolis market rates) + equity. Full package includes:
- New hire RSUs + ESPP stock programs
- Global health insurance covering family
- Free mental health benefits (employees + dependents 6+)
- Professional development + product training
- Mentor/buddy programs + Community Guilds
- Inclusion Talks + internal networking
- Hybrid work + commuter/fitness benefits
Benefits vary by location/employment type. France employees receive locally competitive perks.
Why Join Datadog?
Datadog (NASDAQ: DDOG) delivers growth + profitability in cloud observability. We break down silos, solve cloud complexity, and power digital transformation for customers worldwide. Built by engineers for engineers, used by organizations across industries.
Our people-first culture champions professional development, diversity, innovation, and work excellence. Join a collaborative, pragmatic community solving tough problems, taking smart risks, celebrating success. Experience #DatadogLife via Instagram, LinkedIn, Learning Center.
Work on cutting-edge AI/ML infrastructure powering observability products used by Fortune 500 companies. Hybrid Paris/Sophia Antipolis locations offer tech hub access + quality of life.
How to Apply
Ready to build the future of AI serving at Datadog? Apply now for Senior Software Engineer (MLOps) – Serving. Submit resume highlighting ML infrastructure experience. We'll review applications quickly – top candidates interview within 1 week.
Datadog provides equal opportunity. We celebrate diversity and encourage applications from all backgrounds. Let's build scalable AI together.
Locations
- Paris, France
- Sophia Antipolis, France
Salary
89,250 - 132,000 EUR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- MLOps Engineeringintermediate
- Ray Serving Frameworkintermediate
- Distributed Systemsintermediate
- Python Developmentintermediate
- Go Programmingintermediate
- GPU Optimizationintermediate
- Cloud Observabilityintermediate
- Model Inferenceintermediate
- CI/CD Pipelinesintermediate
- A/B Testingintermediate
- Telemetry Instrumentationintermediate
- Kubernetes Orchestrationintermediate
- Datadog Monitoringintermediate
- LLM Deploymentintermediate
- High-Throughput APIsintermediate
Required Qualifications
- 6+ years of backend or infrastructure engineering experience with 2+ years in ML/AI platforms (experience)
- Proven experience building distributed systems for model serving, realtime inference, or large-scale APIs (experience)
- Proficiency in Python, Go, or systems languages with performance tuning expertise in high-throughput environments (experience)
- Familiarity with Ray, TorchServe, Triton, or BentoML inference-serving frameworks (experience)
- Hands-on experience with GPUs and heterogeneous compute workloads (experience)
- Strong understanding of observability, rollback strategies, and production deployment best practices (experience)
Responsibilities
- Architect high-scale ML and LLM model serving systems across multiple data centers with strong SLAs
- Design and optimize Ray-based inference infrastructure for low- and high-throughput workloads
- Build self-service tools, CI/CD pipelines, and rollback mechanisms for applied scientists
- Implement A/B testing, shadow deployments, and continuous model improvement capabilities
- Collaborate with platform teams on GPU provisioning, traffic routing, and runtime optimization
- Instrument inference workflows with comprehensive telemetry including latency, token counts, and errors
- Ensure production-ready inference endpoints on CPU and GPU environments
- Drive observability and reliability for mission-critical AI platform components
- Enable cross-team model deployment workflows across Datadog's observability products
Benefits
- general: New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
- general: Comprehensive global health insurance for employees and dependents
- general: Free mental health benefits for employees and dependents age 6+
- general: Continuous professional development and product training programs
- general: Intradepartmental mentor and buddy programs for networking
- general: Inclusive company culture with Community Guilds (employee resource groups)
- general: Access to Inclusion Talks and internal panel discussions
- general: Competitive commuter benefits and fitness reimbursements
- general: Hybrid workplace with work-life harmony flexibility
Tags & Categories
Answer 10 quick questions to check your fit for Senior Software Engineer (MLOps) – Serving Careers at Datadog - Paris, France | Apply Now! @ Datadog.
Related Books and Jobs