Senior Software Engineer, MLOps and Infrastructure

London, England, United Kingdom

Auto‑apply with AI Apply

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI & Machine Learning, Enterprise Software, Data & AnalyticsIndustries

Requirements

Candidates should have over 5 years of engineering experience in running production infrastructure at a large scale. They must have experience designing highly available distributed systems with Kubernetes and GPU workloads, as well as familiarity with GCP, Azure, AWS, and/or OCI. Proficiency in designing, deploying, supporting, and troubleshooting complex Linux-based computing environments is essential. Excellent collaboration and troubleshooting skills are required, along with the grit and adaptability to solve evolving technical challenges.

Responsibilities

As a Senior Software Engineer, you will build self-service systems that automate managing, deploying, and operating services. This includes developing custom Kubernetes operators to support language model deployments. You will automate environment observability and resilience, ensuring all developers can troubleshoot and resolve issues. Participation in an on-call rotation to meet defined service level objectives is required. Additionally, you will build strong relationships with internal developers and influence the Infrastructure team's roadmap based on their feedback while fostering team development through knowledge sharing and an active review process.

Skills

Kubernetes

GPU workloads

GCP

Azure

AWS

OCI

Linux

Troubleshooting

System Design

Automation

Observability

Cohere

Provides NLP tools and LLMs via API

About Cohere

Cohere provides advanced Natural Language Processing (NLP) tools and Large Language Models (LLMs) through a user-friendly API. Their services cater to a wide range of clients, including businesses that want to improve their content generation, summarization, and search functions. Cohere's business model focuses on offering scalable and affordable generative AI tools, generating revenue by granting API access to pre-trained models that can handle tasks like text classification, sentiment analysis, and semantic search in multiple languages. The platform is customizable, enabling businesses to create smarter and faster solutions. With multilingual support, Cohere effectively addresses language barriers, making it suitable for international use.

Toronto, CanadaHeadquarters

2019Year Founded

$914.4MTotal Funding

SERIES_DCompany Stage

AI & Machine LearningIndustries

501-1,000Employees

Risks

Competitors like Google and Microsoft may overshadow Cohere with seamless enterprise system integration.

Reliance on Nvidia chips poses risks if supply chain issues arise or strategic focus shifts.

High cost of AI data center could strain financial resources if government funding is delayed.

Differentiation

Cohere's North platform outperforms Microsoft Copilot and Google Vertex AI in enterprise functions.

Rerank 3.5 model processes queries in over 100 languages, enhancing multilingual search capabilities.

Command R7B model excels in RAG, math, and coding, outperforming competitors like Google's Gemma.

Upsides

Cohere's AI data center project positions it as a key player in Canadian AI.

North platform offers secure AI deployment for regulated industries, enhancing privacy-focused enterprise solutions.

Cohere's multilingual support breaks language barriers, expanding its global market reach.

Land your dream remote job 3x faster with AI

Try Jobo Free