Staff Machine Learning Engineer, Gen AI | Voice & Speech
New
J
JobgetherMachine Learning, GenAI
Based in United StatesFull-TimeStaff
SalaryCompetitive compensation package with potential equity participation.
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Job Details
- Experience
- 15+ years
- Required Skills
- AWSPostgreSQLPythonGCPKubernetesMachine LearningGenerative AIDistributed Systems
Requirements
- 15+ years of experience in Machine Learning or Artificial Intelligence, with deep specialization in audio and voice GenAI solutions at scale.
- Demonstrated experience building and deploying production-grade ML-driven B2B, multi-tenant applications serving external customers.
- Mandatory hands-on experience delivering meaningful voice or audio GenAI solutions in production at scale.
- Deep expertise in modern GenAI techniques, including LLMs, RAG, prompt engineering, fine-tuning, model evaluation, and high-scale audio or voice models.
- Experience building low-latency, high-accuracy AI agents and customer-facing GenAI applications.
- Strong expertise in distributed systems architecture, including operating services capable of handling hundreds of millions of transactions and terabytes of data.
- Strong knowledge of scalable relational and NoSQL data platforms, including PostgreSQL, Vitess, Spanner, Bigtable, and Redis.
- Hands-on experience with cloud-native infrastructure on GCP or AWS, including Kubernetes, infrastructure-as-code, and highly available system design.
- Proven ability to lead complex technical initiatives across multiple teams and deliver measurable business outcomes.
- Demonstrated ability to influence without direct authority, build consensus, and communicate sophisticated technical concepts in business terms.
- Experience working in compliance-heavy environments such as healthcare or fintech.
- Strong coaching and mentorship capabilities, with a history of elevating technical standards and developing senior engineering talent.
Responsibilities
- Design and develop scalable ML infrastructure, tooling, services, and models that enable engineering teams to incorporate AI capabilities into customer-facing products.
- Build internal and external platforms that support reliable delivery of generative AI and machine learning features across multiple engineering teams.
- Translate product objectives into actionable technical plans and develop resilient services for data integration, event processing, and AI-powered applications.
- Provide technical guidance to product and engineering teams on data lifecycles, machine learning patterns, architectural tradeoffs, and scalable implementation approaches.
- Write high-quality, performant, maintainable, and testable production code in cloud-native environments.
- Lead cross-team technical initiatives involving ML infrastructure, GenAI, distributed systems, observability, reliability, and engineering excellence.
- Evaluate emerging technologies and industry developments to identify opportunities that create strategic value.
- Establish and influence company-wide standards for architecture, engineering quality, observability, reliability, and scalable distributed systems.
- Mentor Staff and Senior Engineers, strengthen architectural thinking through design reviews and documentation, and help develop future technical leaders.
- Partner across organizational boundaries to build consensus, resolve complex technical challenges, and translate engineering tradeoffs into clear business implications.
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