# Staff ML - GenAI Engineer, Voice & Speech

**Company:** [Weave](https://hotfix.jobs/companies/weave)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 15+ years
**Skills:** Python, Jupyter, Dagster, MLflow, Kubeflow, Dvc, Triton Server, LLMs, RAG, Prompt Engineering, Fine-Tuning, Kubernetes, GCP, AWS, Postgres
**Posted:** 2026-08-06

> Leads development of scalable machine learning infrastructure, models, and internal platforms for voice and speech GenAI products. Requires extensive ML/AI experience, expertise in modern LLM techniques and audio models, distributed systems, cloud deployment, and production-scale data platforms.

## Job Description

## Responsibilities
- Design and develop machine learning infrastructure, tooling, and models for AI-powered products.
- Help product and development teams understand the machine learning data lifecycle and experimentation.
- Build internal products and platforms that enable AI features in customer-facing products.
- Advise teams on machine learning patterns, anti-patterns, tradeoffs, and end-to-end customer experiences.
- Build scalable, resilient services for data integration, event processing, and platform extensions.
- Contribute to product functionality serving large amounts of data and traffic.
- Write high-quality, performant, sustainable, and testable code.
- Coach and collaborate with teammates and stakeholders.
- Work with distributed components and services in cloud environments.
- Translate product goals into actionable engineering plans.

## Requirements
- 15+ years of experience in machine learning or AI, focused on audio and voice generative AI solutions at scale.
- Expertise in LLMs, RAG, prompt engineering, fine-tuning, multimodal models, and LLM evaluations.
- Experience moving and storing terabytes of data or hundreds of millions to billions of records.
- Experience building and deploying production ML-driven B2B, multi-tenant applications at scale.
- Experience with Python, Jupyter, workflow engines such as Dagster, MLflow, and Kubeflow, DVC, Triton Server, LLMs, and PostgreSQL.
- Experience with data labeling or annotation for audio or text use cases.
- Understanding of distributed systems and scalable, redundant, observable services.
- Experience designing systems for distributed datasets and services.
- Experience deploying solutions to public clouds such as AWS or Google Cloud.
- Experience providing stable libraries and SDKs for internal use.
- Demonstrated delivery of complex projects in enterprise production environments.
- Leadership or mentorship experience.
- Strong collaboration, strategic thinking, technical aptitude, and execution skills.

## Nice to Have
- Background in data analysis, visualization, and presentation.
- 14+ years of engineering and systems experience with strong coding and system design proficiency.
- Experience with low-latency natural language models and pipelines.
- Experience with real-time audio models, transcription, ASR pipelines with interruption detection, audio alignment, and speech synthesis.
- Experience with Model Context Protocol (MCP).
- Experience with containers, orchestrators, Kubernetes or GKE, and the Operator Pattern.
- Experience handling PHI and PII data.
- Experience with automation and container-based workflow engines.
- Experience with GitOps, infrastructure as code, and configuration-driven systems.
- Preference for open-source solutions.
- Track record of clean abstractions and simple-to-use APIs.
- Experience rapidly prototyping in greenfield environments and working with evolving problems.

## Compensation and Benefits
- Fully remote opportunity in India.
- Expected overlap with India and US business hours.
- Employment is contingent upon successful completion of a background check.

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