Staff Inference Engineer - AI

Thomson Reuters • Eagan, MN

3d • Hybrid

About The Position

Thomson Reuters is seeking a Staff Inference Engineer to productionize, optimize, and scale AI and large language model workloads that power its AI-driven products. The role ensures models—from classical machine learning to generative AI—run efficiently across the company’s multi-cloud environment and internal Kubernetes clusters, meet enterprise reliability requirements, and integrate with its data backbone and production APIs.

The engineer will work with Platform Engineering, Enterprise AI Services, cloud and data engineering, Product, Data Science, Architecture, and AI teams to bring research models into production and build the next generation of AI infrastructure. This includes optimizing inference performance and compute use, building scalable containerized pipelines, implementing routing and failover, and maintaining observability, governance, and reliability for enterprise AI services.

The position uses a hybrid work model for office-based roles. Thomson Reuters describes flexible work arrangements, including the option to work from anywhere for up to eight weeks per year.

Requirements

• At least 7 years of relevant experience.
• Strong understanding of machine-learning and LLM fundamentals and inference optimization techniques.
• Hands-on experience with GPU programming; CUDA is preferred.
• Experience with inference runtimes such as TensorRT and ONNX Runtime.
• Experience with deep-learning frameworks such as PyTorch or TensorFlow.
• Proficiency in Python and at least one systems programming language; C++ is strongly preferred for performance-critical inference paths.
• Experience deploying AI workloads to AWS, GCP, or Azure and Kubernetes.

Nice To Haves

• Familiarity with vector search systems, including OpenSearch vectors, and retrieval-augmented generation pipelines.
• Knowledge of distributed systems, microservices, CI/CD, and cloud-native architecture.

Responsibilities

• Optimize LLMs and machine-learning models for high-performance inference using techniques such as quantization, pruning, distillation, and hardware-specific tuning.
• Deploy and scale GPU inference workloads across AWS, Azure, GCP, and internal Kubernetes clusters, with predictable performance during peak traffic and business hours.
• Implement routing and failover strategies for OpenAI, Anthropic, and Vertex AI traffic.
• Integrate models into production-grade APIs for Thomson Reuters products and enterprise workflows.
• Optimize inference environments and eliminate performance bottlenecks to reduce latency.
• Collaborate with Platform Engineering teams across Landing Zones, Network, Storage, Compute, and AI to align inference workloads with cloud-native patterns.
• Build and optimize containerized inference pipelines using Kubernetes for large-scale distributed workloads.
• Ensure deployments, monitoring, governance, and drift detection comply with Thomson Reuters AI standards.
• Profile inference performance, identify GPU and CPU bottlenecks, and optimize compute utilization across heterogeneous hardware.
• Implement observability and health monitoring for inference pipelines to support reliable enterprise AI services.
• Collaborate with AI engineers on quantization techniques, numerical precision improvements, and non-standard architectures.
• Support scaling AI infrastructure for critical releases and global product rollouts.
• Partner with cloud engineers across Azure, AWS, and GCP to develop guardrails and automation for inference workloads.
• Collaborate with platform teams to improve AI workload capacity forecasting and onboard research models into production.

Benefits

• Flexible vacation and paid time off, including sick and safe leave and paid holidays.
• Two company-wide Mental Health Days off annually.
• Access to the Headspace app and Employee Assistance Program.
• Retirement savings plan, including a competitive 401(k) plan with company match for eligible US employees.
• Tuition reimbursement.
• Employee incentive programs and potential eligibility for an annual bonus based on enterprise and individual performance.
• Health, dental, vision, disability, and life insurance programs.
• Parental leave and sabbatical leave.
• Flexible Spending and Health Savings Accounts.
• Fitness reimbursement.
• Commuter benefits.
• Adoption and surrogacy assistance.
• Employee Stock Purchase Plan.
• Two paid volunteer days annually and opportunities for pro-bono consulting and ESG initiatives.
• Flexible work arrangements, including working from anywhere for up to eight weeks per year.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed