Responsibilities
- 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.
Requirements
- 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.
Nice to Have
- A background with data analysis, visualization, and presentation.
- 3+ 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.
- Experience with automation and container based workflow engines.
- Experience with GitOps, IaC, and configuration driven systems.
- A preference for open source solutions.
- A track record of clean abstractions and simple to use APIs.
- A desire to advance the state of the art with new and innovative technologies.
- Enjoys working in a greenfield environment using rapid prototyping.
- Enjoys working with open-ended, evolving problems, and domains.
Additional Information
- This is a fully remote opportunity in India with expectancy to overlap the India and US business hours
