Staff Machine Learning Engineer, Gen AI

8+ years of experience in Machine Learning or AI, preferably with a focus on natural language Experience moving and storing TBs of data or 100M’s to 10B’s of records Experience building and deploying ML driven B2B multi-tenant applications in production environments at scale for external products and customers Experience with common ML technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others Experience with modern ML tools, techniques, and evaluation such as LLMs, RAG, Prompt Engineering, Fine Tuning, LLM evaluations, multi-modal models, and others Experience with data labelling or annotation for audio or text use cases Understanding of distributed systems and building scalable, redundant, and observable services Expertise in designing and architecting systems for distributed data sets and services Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.) Experience providing stable well designed libraries and SDKs for internal use Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments Demonstrated experience working with varied stakeholders across multiple teams Demonstrated leadership experience leading large projects or teams Strategic thinker with a strong technical aptitude and a passion for execution

Design and Develop machine learning infrastructure, tooling, and models Help product and development teams understand the data lifecycle and the inherent experimental nature of machine learning Build internal products and platforms to enable teams to incorporate AI into their features and customer facing products Consult with teams to help them understand common patterns, anti-patterns, and tradeoffs of machine learning Build scalable, resilient services to support data integration, event processing, and platform extensions Contribute to the continued evolution of product functionality that services large amounts of data and traffic Write code that is high-quality, performant, sustainable, and testable Coach and collaborate inside and outside the team Work in a cloud environment, considering the implementation of functionality through several distributed components and services Work with our stakeholders to translate product goals into actionable engineering plans