Senior ML - GenAI Engineer, Voice & Speech
Weave · Remote · US Remote ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Senior level role
- Fully remote (US)
- GenAI & Voice focus
- Python, Go, Java
- LLMs & RAG experience
Join Weave's Machine Learning Team to democratize AI tools for developers building data-intensive applications. You will design infrastructure, tooling, and models that enable cross-functional teams to integrate AI features safely and at scale.
The team operates autonomously within an agile structure, focusing on distributed systems and scalability. You will collaborate with product owners and engineers to translate goals into actionable plans while handling data for hundreds of millions of users daily.
What you'll do
- Design and develop ML infrastructure, tooling, and models for product teams
- Build internal platforms to help teams incorporate AI into customer-facing features
- Consult with stakeholders on ML patterns, trade-offs, and data lifecycle management
- Construct scalable services for data integration, event processing, and platform extensions
- Write high-quality, performant, and testable code for distributed cloud environments
- Coach colleagues and share expertise to foster best practices across the organization
- Translate product goals into engineering plans and execute complex projects on time
What you'll need
- 5+ years of experience in structured back-end languages like Go, Java, or Python
- Experience managing TBs of data or datasets with 100M to 10B records
- Proven track record deploying ML-driven B2B multi-tenant applications in production
- Proficiency with ML tools such as Jupyter, Dagster, MLflow, Kubeflow, and DVC
- Knowledge of modern techniques including LLMs, RAG, prompt engineering, and fine-tuning
- Experience with data labeling or annotation for audio and text use cases
- Strong understanding of distributed systems and building observable, redundant services
- Experience building solutions on public clouds like AWS or GCP
Nice to have
- 3+ years in data science, machine learning, or predictive analytics
- Experience with real-time audio models, ASR pipelines, and speech synthesis
- Knowledge of natural language models, embeddings, and production inference at scale
- Familiarity with Model Context Protocol (MCP) and emerging AI technologies
- Expertise in Kubernetes, GKE, containers, and service meshes at scale
- Experience handling sensitive data such as PHI under HIPAA or PII regulations
- Background in GitOps, Infrastructure as Code, and configuration-driven systems
Stack
- Python
- Go
- Java
- Jupyter
- Dagster
- MLflow
- Kubeflow
- DVC
- Triton Server
- LLMs
- Postgres
- AWS
- GCP
- Kubernetes
How you'll work
- Fully remote within the United States
- Optional office access near Lehi, UT headquarters
- Reports to the Engineering Director
- Cross-functional agile team structure
Hiring process
- Employment contingent on successful background check completion
- AI tools may assist in scheduling interviews and reviewing applications