Weave is looking for a Senior Machine Learning Engineer to join their self-empowered team and contribute to the development of machine learning infrastructure, tooling, and models. The ideal candidate will have 5+ years of experience in a structured back-end language and experience building and deploying ML driven B2B multi-tenant applications.
Requirements
- 5+ years of experience in any structured back-end 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
- 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, 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
- Strategic thinker with a strong technical aptitude and a passion for execution
- A background with data analysis, visualization, and presentation
- 3+ years of experience in data science, machine learning, or predictive analytics in addition to engineering experience
- Experience with natural language models, embeddings, and inference in production, 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 including networking, storage, service meshes, and multi-cluster communication. 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
- Deep understanding of distributed data technologies such as streaming, data mesh, data lakes, warehouses, or distributed machine learning
- 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
Benefits
- Equal opportunity employer
- Committed to fostering an inclusive workplace
- Welcomes anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics
