Thomson Reuters
SeniorSoftwareEngineer,AI(C#,Cloud)
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“Senior Software Engineer, AI (C#, Cloud) at Thomson Reuters. Skills: Machine learning, Deep learning, Inference optimization, Cloud native. Optimize LLMs and ML models. Deploy inference workloads on GPUs”
Industry & Context.
Performance optimizations; Eliminate performance bottlenecks; Identify GPU/CPU bottlenecks; Optimize compute utilization
What They're Looking For.
Must Have
ML/LLM fundamentals, AI workloads to AWS/GCP/Azure and Kubernetes, C#, GPU programming, Inference runtimes, Deep learning frameworks, Python, Systems language, Vector search systems, Retrieval augmented generation pipelines, Distributed systems, Microservices, CI/CD, Cloud native architecture, AI networks, GPU, Multithreading, Accelerators with vectorized instructions, Model compression, Hardware aware model optimizations, Hardware accelerators architecture, GPU/ASIC architecture, Machine learning compilers, High performance computing, Performance optimizations, Numerics, SW/HW co-design
Nice to Have
3+ years production experience deploying ML/LLM models at scale, Managing GPU fleets or inference clusters, Supporting enterprise grade AI workloads
What You'll Do.
Optimize LLMs and ML models
Deploy inference workloads on GPUs
Scale inference workloads on GPUs
Implement routing strategies
Implement failover strategies
Integrate models into production grade APIs
Develop highly optimized environments
Eliminate performance bottlenecks
Collaborate with Platform Engineering teams
Ensure inference workloads align with TR’s cloud native
Build containerized inference pipelines
Optimize containerized inference pipelines
Ensure compliance with TR’s AI standards
Profile inference performance
Identify GPU/CPU bottlenecks
Optimize compute utilization
Implement observability for inference pipelines
Implement health monitoring for inference pipelines
Enhance capacity forecasting for AI workloads
Onboard new research models into production
Invent new quantization techniques
Improve numerical precision
Explore non-standard architectures
Develop guardrails for inference workload
Develop automation for inference workload
Support scale out of AI infrastructure
Support global product rollouts
How You'll Work.
Team & Collaboration
Platform Engineering teams; Product teams; Data Science teams; Architecture teams; Enterprise AI teams; AI engineers; Cloud Engineers
Full Job Description
Thomson Reuters is seeking a Senior Software Engineer, AI (C#, Cloud). This role is for someone who has specialized experience in machine learning/deep learning domains such as model compression, hardware aware model optimizations, hardware accelerators architecture, GPU/ASIC architecture, machine learning compilers, high performance computing, performance optimizations, numerics or SW/HW co-design. **About the Role** As a **Senior Software Engineer, AI (C#, Cloud)** , you will: * Optimize LLMs and ML models for high-performance inference using techniques such as quantization, pruning, distillation, and hardware specific tuning * Deploy and scale inference workloads on GPUs across AWS, Azure, GCP and internal Kubernetes clusters, ensuring predictable performance during peak traffic hours, especially during business hours * Implement routing and failover strategies for OpenAI/Anthropic/Vertex AI traffic * Integrate models into production grade APIs supporting TR products and enterprise workflows. * Develop highly optimized environment and eliminate performance bottlenecks to reduce latency * Collaborate with Platform Engineering teams (Landing Zones, Network, Storage, Compute, AI) to ensure inference workloads align with TR’s cloud native patterns (AWS, Azure, GCP, OCI) * Build and optimize containerized inference pipelines using Kubernetes for large‑scale distributed workloads * Ensure compliance with TR’s AI standards for deployment, monitoring, governance, and drift detection * Profile inference performance, identify GPU/CPU bottlenecks, and optimize compute utilization across heterogeneous hardware * Implement observability and health monitoring for inference pipelines, ensuring reliability of enterprise AI services. * Collaborate with platform teams to enhance capacity forecasting for AI workloads * Work with Product, Data Science, Architecture, and Enterprise AI teams to onboard new research models into production * Collaborates closely with AI engineers to inv
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