Senior Machine Learning Engineer

Zendesk is a company focused on customer service software, powering billions of conversations with well-known brands. The role is within the AI Copilot organisation, which develops a multi-million ARR product integrating AI into customer service workflows. Zendesk supports a hybrid working model with offices worldwide and offers flexibility for remote work.

• 5+ years of experience in software engineering with a focus on ML engineering, MLOps, or building ML-powered products.
• Fluent in Python; working proficiency in Ruby is a plus.
• Experience building and operating ML systems in production, including model serving, inference pipelines, and monitoring.
• Experience integrating LLMs into production systems, including prompt engineering, evaluation, or multi-provider setups.
• Comfortable with SQL and data infrastructure, including data pipelines, transformations, and data quality.
• Experience with containerised deployments (Docker, Kubernetes) and cloud infrastructure (AWS).
• Proven track record of owning features end-to-end and delivering them to production with high quality.
• Ability to work with uncertainty and adapt to changing priorities.
• Strong collaboration skills with scientists, product engineers, and product managers.

Nice to have:

• Experience with Snowflake and dbt for data transformations and analytics.
• Hands-on experience with ML pipeline tooling (e.g., Metaflow) and experiment tracking (e.g., MLflow).
• Experience with model serving frameworks (e.g., BentoML) on Kubernetes.
• Familiarity with ML frameworks such as PyTorch or TensorFlow.
• Experience with event-driven architectures (e.g., Kafka).
• Experience with iterative, metrics-driven product development (A/B testing, feature flags, incremental rollouts).

• Own and deliver ML-powered product features end-to-end, including data pipelines, model integration, serving, monitoring, and iteration in production.
• Work closely with scientists to productionise research outputs into reliable, user-facing features.
• Build and maintain ML infrastructure such as model serving, inference pipelines, LLM integrations, and evaluation frameworks.
• Contribute to technical design discussions and architecture decisions within the team and across teams.
• Collaborate with product software engineers to integrate ML capabilities into the broader product experience.
• Improve reliability, performance, and cost-efficiency of ML systems by proactively identifying and addressing issues.
• Mentor more junior engineers through code review, pairing, and knowledge sharing.

Zendesk is an equal opportunity employer committed to diversity, equity, and inclusion. The company uses AI or automated decision systems to screen or evaluate applications in accordance with company guidelines and applicable law. Reasonable accommodations are available for applicants with disabilities.