# Senior ML - GenAI Engineer, Voice & Speech **Company**: Weave **Location**: US Remote **Work arrangement**: remote **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Technology **Apply**: https://jobs.ashbyhq.com/weave/df4c4089-56e1-4055-849e-3e7b13933cbc?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_d26959af-16e ## Description Weave is looking for a Senior ML - GenAI Engineer, Voice & Speech to join their team. 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. As a Machine Learning Engineer on the team, you'll be building models for new products with emerging technologies, at scale. **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 trade-offs 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. **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 any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus). - Experience moving and storing TBs of data or 100 M to 10 B 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, multimodal 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 experience working in enterprise-grade production environments. - Strategic thinker with a strong technical aptitude and a passion for execution. **Nice to Have** - A background in 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, is 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. ## Skills ### Required - Go - Java - Python - Jupyter - Workflow Engines - DVC - Triton Server - LLMs - Postgres - Distributed Systems - Cloud Computing - Machine Learning ### Nice to have - Natural Language Models - Embeddings - Inference - Real-time Audio Models - Voice Use Cases - Model Context Protocol (MCP) - Kubernetes - GKE - Operator Pattern - GitOps - IaC - Configuration-driven Systems --- Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/weave/df4c4089-56e1-4055-849e-3e7b13933cbc?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)