Staff Machine Learning Engineer, Gen AI | Voice & Speech in Abbeyville, Colorado at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Machine Learning Engineer, Gen AI | Voice & Speech based in United States.

This is a senior technical leadership opportunity focused on advancing generative AI across voice, audio, and machine learning products at scale.
You will shape the architecture, infrastructure, and engineering practices that enable teams to deliver sophisticated AI-powered customer experiences.
The role combines deep hands-on expertise with cross-functional influence, helping engineering teams make sound decisions around ML platforms, data, and distributed systems.
You will work on production-grade solutions supporting high-volume, customer-facing applications in a cloud-native environment.
A major focus will be on voice and audio GenAI, including LLMs, RAG, prompt engineering, fine-tuning, model evaluation, and AI agents.
You will also mentor senior technical talent, establish engineering standards, and lead initiatives that have measurable business and organizational impact.
This role is ideal for an accomplished ML engineer who can bridge advanced AI research and scalable product engineering while influencing technical strategy across an organization.

• 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, separating meaningful advances from hype and identifying opportunities that can 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.
• Drive initiatives that improve the scalability and reliability of AI platforms while delivering measurable outcomes for customers and the broader business.

• 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, rather than solely research or experimental exposure.
• Deep expertise in modern GenAI techniques, including LLMs, Retrieval-Augmented Generation (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 technologies such as 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 across organizational boundaries, and communicate sophisticated technical concepts in business terms.
• Experience working in compliance-heavy environments such as healthcare or fintech, with an understanding of how regulatory requirements influence technical architecture and product development.
• Strong coaching and mentorship capabilities, with a history of elevating technical standards and developing senior engineering talent.
• Excellent technical communication skills, with external leadership experience such as open-source contributions, conference presentations, or published technical content considered a plus.
• A collaborative leadership style that combines strong technical convictions with openness to alternative approaches and better ideas.

• Competitive compensation package with potential equity participation.
• Fully remote work opportunity within the United States.
• Flexible, remote-first working environment designed to support autonomy and sustainable performance.
• Opportunity to work on advanced GenAI, voice, audio, and machine learning technologies at significant production scale.
• High-impact technical leadership role with influence across engineering, product, and organizational strategy.
• Opportunity to mentor senior technical professionals and help shape engineering standards and capabilities.
• Exposure to complex distributed systems, cloud infrastructure, AI platforms, and customer-facing applications.
• Inclusive workplace committed to equal opportunity and supporting employees with diverse backgrounds and perspectives.
• Accommodation support available for candidates who require assistance during the hiring process.
• Employment is subject to successful completion of a background check in accordance with applicable laws.