Machine Learning Research Engineer

Create systems for Agentic development, including mechanisms to guide and enhance state-of-the-art LLMs Expert knowledge of Agentic AI and Generative AI capabilities Assess where best-in-class industry capabilities can help undertake operational workflows Invent novel capabilities based on rapid research iterations Work with other engineers to understand and solve challenges Strong Python and engineering skills Demonstrate problem-solving and project management skills to analyse workflows and design automated solutions Thrive in a collaborative environment Experience working in a fully remote, international team (preferred) Experience with Temporal or similar workflow orchestration platforms (preferred) Previous startup experience (preferred) Experience with MLOps practices and tools, and monitoring machine learning systems in production (preferred) Knowledge of browser-based automation methods, such as playwright (preferred) Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD (preferred) Proficiency with SQL and NoSQL databases (preferred) Worked with Kubernetes and infrastructure as code (IaC) tools such as Terraform (preferred)

Design and build capabilities that create Virtual Agents - an 'Agent Factory' Robustly evaluate the agent creation process, allowing systematic improvement through experimentation Implement code generation capabilities, guardrails, and evaluations for encoding workflows Drive uptake of these capabilities with customer-facing technical teams Utilize best-in-class capabilities to deliver new features Research, invent, and create novel capabilities where industry gaps exist Participate in the machine learning community to influence technology implementation Contribute full-stack development, including software engineering, DevOps, and MLOps Manage tasks and projects to ensure capabilities deliver value early