Staff ML Engineer, GenAI, Voice & Speech

Weave

Staff ML Engineer building scalable voice and speech GenAI infrastructure for Weave’s AI-powered products. Designing models, platforms, and distributed services for high-volume customer experiences.

Posted 8/6/2026full-timeRemote • 🇮🇳 IndiaLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in Machine Learning and AI, particularly in audio and voice GenAI solutions, with a strong focus on building scalable, resilient services and deploying ML-driven applications. Proficient in translating product goals into actionable engineering plans while mentoring and collaborating with cross-functional teams.

Highest-signal resume keywords

Machine Learning ExpertiseAudio/Voice GenAI SolutionsPython ProgrammingDistributed Systems UnderstandingCloud Deployment Experience

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAI DevelopmentLLMsPrompt EngineeringData IntegrationScalable ApplicationsReal-Time Audio ModelsSystem DesignData AnalysisAutomation

Soft Skills

LeadershipMentorshipCollaborationStrategic ThinkingExecution Focus

Tools & Technologies

PythonJupyterDagsterMLFlowKubeFlowTriton ServerPostgresKubernetesGKEGitOps

Industry Keywords

B2B ApplicationsData LifecycleHIPAA CompliancePII DataMultimodal ModelsASR PipelinesModel Context ProtocolEvent ProcessingContainerizationWorkflow Engines

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsGoogle Cloud PlatformKubernetesPostgresPython

About the role

Key responsibilities & impact

Design and develop machine learning infrastructure, tooling, and models for product experiences
Help product and development teams understand the machine learning data lifecycle and experimentation
Build internal products and platforms enabling AI features in customer-facing products
Consult 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
Evolve product functionality serving large amounts of data and traffic
Write high-quality, performant, sustainable, and testable code
Coach and collaborate with colleagues across and outside the team
Work with distributed components and services in cloud environments
Translate product goals into actionable engineering plans with stakeholders
Report to the Manager, Machine Learning

Requirements

What you’ll need

15+ years of experience in Machine Learning or AI, focused on or specializing in audio and voice GenAI solutions at scale
Deep expertise in LLMs, RAG, prompt engineering, fine-tuning, high-scale audio/voice models, and LLM evaluations
Experience moving and storing terabytes of data or hundreds of millions to billions of records
Experience building and deploying scalable ML-driven B2B multi-tenant applications in production for external customers
Experience with Python, Jupyter, workflow engines such as Dagster, MLFlow, and KubeFlow, DVC, Triton Server, LLMs, and Postgres
Experience with multimodal models, data labeling or annotation for audio or text use cases
Understanding and expertise in distributed systems, scalable redundant observable services, and distributed data sets
Experience deploying solutions on public clouds such as AWS or GCP
Experience providing stable libraries and SDKs for internal use
Track record delivering complex projects on time in enterprise-grade production environments
Demonstrated leadership or mentorship capacity
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, ASR pipelines with interruption detection, audio alignment, and speech synthesis
Experience with Model Context Protocol (MCP)
Understanding of containers, orchestrators, and usage patterns at scale
Experience with Kubernetes or GKE and the Operator Pattern is a plus
Experience with PHI/HIPAA and PII data
Experience with automation and container-based workflow engines
Experience with GitOps, infrastructure as code, and configuration-driven systems
Background in data analysis, visualization, and presentation is a plus
Self-driven, strategic, execution-focused, and willing to learn in a quickly changing industry
Must successfully complete a background check

Benefits

Comp & perks

Fully remote opportunity in India
Opportunity to work on AI-powered applications and emerging machine learning technologies
Cross-functional, highly autonomous agile team environment
Coaching and collaboration opportunities
Inclusive workplace and equal opportunity employment
Disability or special-needs accommodation
Background check conducted in accordance with applicable laws