Staff Software Engineer (Inference Infrastructure)

• We are looking for Members of Technical Staff to join the Model Serving team at Cohere

• The team is responsible for developing, deploying, and operating the AI platform delivering Cohere’s large language models through easy to use API endpoints

• In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments

• You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs

Benefits

• Six weeks’ paid vacation

• Equity / stock options

• RRSP, 401(k), and Pension Scheme contributions

• Coverage for 100% of your insurance premiums across health, dental, vision, and travel

• Additional coverage for accessing mental health providers/services

• Six months of fully paid parental leave, including adoption and surrogacy

• Financial support for egg freezing and IVF in Canada and the UK

• A monthly fitness and wellness allowance

• Globally dispersed company that supports a remote work culture

• A $2,000 annual education benefit for professional development

• A weekly stipend for meals when working remotely and catered lunch when working from one of our global offices

• A monthly arts and culture allowance

• A monthly quality time allowance- Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications?

• Strong understanding or working experience with distributed systems

• 5+ years of engineering experience running production infrastructure at a large scale

• Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving

• Excellent collaboration and troubleshooting skills to build mission-critical systems, and ensure smooth operations and efficient teamwork

• The grit and adaptability to solve complex technical challenges that evolve day to day

• Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters

• Experience in Golang, C++ or other languages designed for high-performance scalable servers)

• Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), especially how they influence latency and throughput of inference

• Experience in compute/storage/network resource and cost management

• Experience with Kubernetes dev and production coding and support

• If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

• Experience in designing, deploying, supporting, and troubleshooting in complex Linux-based computing environments