Staff Machine Learning Engineer

About the Role

Weave is looking for engineers hungry for fun challenges who can join our self-empowered teams and contribute in both technical and non-technical ways. You will be joining a team of talented developers that share a common interest in distributed backend systems, data, scalability, and continued development. You will get a chance to apply these, and other skills, to new and ongoing projects to make machine learning more approachable, data more available, and easier to discover and use by helping design how teams build out AI powered features at Weave.

Our teams are cross-functional agile teams composed of a product owner, backend and frontend devs and devops. Teams are highly autonomous with the ownership and ability to act in Weave’s best interest. Above all, your work will impact the way our customers experience Weave while working closely with a highly skilled team to accomplish varying goals and cultivate our phenomenal culture.

Location Type: Remote Employment Type: FullTime

Team Purpose

The Machine Learning Team's mission is to enable product innovation by making it painless for developers to build AI powered applications that require access to large sets of data. Machine learning is challenging but we are striving to democratize access to the tools and technology that powers it so teams can build cutting edge features safely and responsibly without a PhD in Data Science. As a Machine Learning Engineer on the team you’ll be building models for new products with emerging technologies, at scale. We handle data for hundreds of millions of people daily.

This is a fully remote opportunity in India with expectancy to overlap the India and US business hours.

Reports to: Engineering Director

What You Will Own

• 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.
• 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.