# Senior ML - GenAI Engineer, Voice & Speech

**Company:** [Weave](https://hotfix.jobs/companies/weave)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** Python, Jupyter, Dagster, MLflow, Kubeflow, Dvc, Triton Server, LLMs, Retrieval-Augmented Generation, Prompt Engineering, Postgres, Kubernetes, GCP, AWS, GitOps
**Posted:** 2026-03-10

> Build and deploy scalable machine learning infrastructure, models, and AI platforms for voice, speech, and natural-language products. The role requires 5+ years in ML or AI, production experience with large-scale data and multi-tenant applications, and expertise in distributed cloud systems.

## Job Description

## Responsibilities
- Design and develop machine learning infrastructure, tooling, and models for product teams.
- Help product and development teams understand the machine learning data lifecycle and experimental processes.
- Build internal products and platforms that enable AI-powered customer features.
- 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 volumes of data and traffic.
- Write high-quality, performant, sustainable, and testable code.
- Coach and collaborate with colleagues and stakeholders.
- Design and implement functionality across distributed cloud components and services.
- Translate product goals into actionable engineering plans.

## Requirements
- 5+ years of experience in machine learning or AI, preferably focused on natural language.
- 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 data labeling or annotation for audio or text use cases.
- Understanding of distributed systems and scalable, redundant, observable services.
- Expertise designing systems for distributed datasets and services.
- Experience deploying solutions on public clouds such as AWS or Google Cloud.
- Experience providing stable libraries and SDKs for internal use.
- Demonstrated delivery of complex projects in enterprise-grade production environments.
- Leadership or mentorship experience.
- Strong collaboration, communication, strategic thinking, and execution skills.

## Nice-to-haves
- Data analysis, visualization, and presentation experience.
- 3+ years of engineering and systems experience with strong coding and system design proficiency.
- Experience with low-latency natural language models and pipelines at scale.
- Experience with real-time audio models and voice use cases, including transcription, automatic speech recognition pipelines with interruption detection, audio alignment, and speech synthesis.
- Experience with Model Context Protocol (MCP).
- Experience with containers, orchestrators, Kubernetes, Google Kubernetes Engine, 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 and simple, clean abstractions and APIs.
- Experience rapidly prototyping in greenfield environments and working with evolving problem domains.

## Compensation and Benefits
- Fully remote opportunity in India.
- Expected overlap with India and US business hours.

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