Senior ML - GenAI Engineer, Voice & Speech

• Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences.

• 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. Guide them through creating excellent customer experiences end to end.

• 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 while holding yourself accountable for the quality of the code you produce.

• Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.

• 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.

What You'll Need to Accomplish the Job

• High integrity, team-focused approach, and collaboration skills to build tight-knit. relationships across Weave with various roles and stakeholders.

• Responsive person with a strong bias for action.

• 5+ 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 and techniques 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 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.

• Self driven and a thirst for learning in a quickly changing industry.

• Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments.

• Demonstrated capacity for leadership or mentorship.

  • Strategic thinker with a strong technical aptitude and a passion for execution.