Weave is hiring a Staff Machine Learning Engineer, Gen AI to join our Machine Learning Team. In this role, you will drive product innovation by democratizing AI tools and building models with emerging technologies at scale. You will design our ML infrastructure, consult with product teams, and build internal platforms to help incorporate AI into our customer-facing products.
What You'll Do
- 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 We're Looking For
- 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 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.
- 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 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.
Nice to Have
- A background with data analysis, visualization, and presentation.
- 5+ 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 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.
Technical Stack
- Python, Jupyter, Dagster, MLFlow, KubeFlow, DVC, Triton Server, LLMs
- Postgres, AWS, GCP, Kubernetes, GKE
Team & Environment
You will join cross-functional agile teams composed of a product owner, backend and frontend devs and devops. Teams are highly autonomous and you will report to an Engineering Director.
Work Mode
This role is open to candidates based in India.
Weave is an equal opportunity employer committed to fostering an inclusive workplace where all individuals are valued and supported.
