Jobs at Cohere AI

Build and ship native iOS and Android features for Cohere’s secure AI workspace platform. Collaborate with designers and researchers to implement interfaces, productionize AI models, research technologies, and develop privacy- and security-focused tooling, including custom solutions when standard libraries are unsuitable. The role requires experience with Kotlin and Swift, production mobile applications, project bootstrapping, cross-codebase debugging, and execution in fast-changing environments. Audio feature experience is a bonus.

Build and ship features for Cohere’s North AI workspace platform, develop autonomous agents that interact with sensitive enterprise data, and deploy highly performant, secure applications in low-resource environments. Collaborate with researchers to productionize advanced AI models and techniques while contributing across the full stack using Python and React.

Evaluate and rank multimodal model outputs, stress-test and document failures, author and edit dataset prompts/responses, build and apply rubrics, perform high-quality annotations across text, image, and structured formats, participate in calibration checks, adapt to evolving tasks, and report model performance trends to cross-functional teams.

Drive analytics and measurement for AI product adoption and impact. Build agentic analytics, small language models, predictive models, and customer-facing insights. Design and run experiments (A/B tests, causal inference), ship production models, and translate ambiguous business questions into actionable recommendations used by product, sales, and leadership.

The Senior ML Systems Engineer will build and maintain the training framework for large-scale language models, focusing on distributed training and performance optimization.

The Research Intern will conduct machine learning research, focusing on large language models, and disseminate results through publications and code while collaborating with Cohere researchers.

Build and maintain integrations for North's agentic platform, own the end-to-end integration pipeline, create evals and tests to ensure reliability, tune tool descriptions, and help other engineers add and maintain integrations while using AI responsibly to improve performance and quality.

Build and ship full‑stack features for North, an enterprise AI workspace. Develop secure autonomous agents, execution engines, integrations, observability and evaluation systems. Collaborate with researchers to productionize models and deliver performant, low‑resource deployment code while adhering to strict security and privacy constraints.

Lead the deployment of North in private cloud environments, collaborating with IT teams, designing strategies, and resolving technical issues.

Lead global tax planning and M&A tax due diligence, design tax-efficient cross-border and transfer pricing structures, oversee Canadian income tax compliance and filings, advise Legal and business teams on commercial tax implications, and monitor international tax developments to optimize Cohere's tax position.

Build and ship LLM- and agent-powered product experiences for North, designing interfaces, evals, observability, and feedback loops to improve reliability and user outcomes. Collaborate with modelling, product, design, and customers to turn failures and feedback into measurable product and model improvements.

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.

Lead North's integrations strategy and execution: prioritize, ship, and drive adoption of connectors and ecosystem tooling. Partner with customers and engineering to convert integrations into reusable platform capabilities (auth, connector framework, data sync, permissions). Define developer/partner experience (APIs, SDKs, plugins) and instrument analytics to measure adoption, time-to-stand-up, and retention.

The Staff Software Engineer will develop and deploy high-performance machine learning systems, optimizing large language models for production environments. Responsibilities include ensuring high availability and low latency for AI applications and working collaboratively across teams.

The Site Reliability Engineer will develop, deploy, and operate AI infrastructure, focusing on high-performance and scalable machine learning systems using Kubernetes and cloud platforms.

As a Forward Deployed Engineer, you will build and ship features for an AI workspace platform, develop autonomous agents, and manage end-to-end deployments, collaborating closely with clients in various sectors.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

Lead strategic sourcing and procurement for professional services categories, including consulting, marketing, legal, communications, and other external services. Manage end-to-end procurement, RFPs, vendor negotiations, category strategies, contracts, supplier performance, compliance, savings initiatives, and purchase-to-pay processes. Collaborate with FP&A, Accounting, Legal, and business stakeholders while maintaining documentation, controls, and performance reporting.

Owns revenue enablement programs for North American field teams from design through rollout, measurement, and iteration. Partners with Product, Marketing, Sales Leadership, and RevOps to align go-to-market priorities. Develops playbooks, certifications, training, and competitive resources; operationalizes MEDDPICC; tracks enablement KPIs; improves content platforms and AI workflows; coaches sellers; and translates field insights into updated enablement materials.

Build and maintain internal applications that support annotators, ML researchers, product managers, and other stakeholders. Develop user-facing browser and server experiences using full-stack technologies, design resilient mission-critical systems, improve engineering velocity, and collaborate through pairing, architecture, documentation, and technical talks. The role requires comfort across frontend and backend development, complex SQL, stakeholder collaboration, and adoption of new technologies.