Staff ML - GenAI Engineer, Voice & Speech

About this role

Weave is looking for a Staff Engineer to join the Machine Learning Team specialised in voice and audio modalities, where you will be at the forefront of enabling product innovation and building AI-powered applications. In this role, you will help design how teams across Weave build out AI-powered features, serving as a technical leader who bridges the gap between sophisticated machine learning and practical, customer-facing products.

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.

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 buildcutting-edgee 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 the expectation to overlap with India and US business hours.s

- Reports to: Manager, Machine Learning

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.

- 15+ years of experience in Machine Learning or AI, with a focus on or expertise in audio and voice GenAI solutions at scale

- Deep expertise with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, Fine-tuning, and specifically high-scale audio/voice models and LLM evaluations

- Experience moving and storing TBs of data or100 Ms to 110 Brecords.

- 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 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.

What Will Make Us Love You

- A background with data analysis, visualisation, and presentation.

- 14+ years of experience in engineering and systems with strong proficiency in coding and system design.

- Experience with low-latency natural language models and pipelines at scale.

- Experience with real-time audio models and voice use cases such as transcription, ASR pipelines with interruption detection, audio alignment, and speech synthesis.

- Experience with emerging technologies such as Model Context Protocol (MCP).

- Proficient understanding of containers, orchestrators, and usage patterns at scale. Experience with Kubernetes or GKE and the Operator Pattern (GCP), specifically, a plus.

- Experience with highly sensitive data such as PHI (HIPAA) and PII data.

…