Staff Machine Learning Engineer - voice AI

You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that anyuser, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers, and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.

Responsibilities:

• Contribute to the design, development and implementation of the core Voice Platform (Audio Acquisition, Conversation Management, Speech Generation, integration with API and self-hosted Voice AI models, Voice Harness).
• Partner with product managers to work with customers, understand their use cases and technology challenges, and build for their success.
• Build and deploy large Voice AI distributed systems at scale spanning multiple regions and data centres.
• Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc. )
• Contribute to the continuous improvement of the SRE practice by turning operational use cases into requirements for software tooling.
• Be a mentor for colleagues and help promote knowledge-sharing across Voice AI engineering disciplines.

Requirements:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
• This may include using AI-powered tools, automating workflows, analysing AI-driven insights, or exploring AI's potential impact on the function or industry.
• 8+ year of relevant industry experience.
• Hands-on experience building distributed Voice AI systems at a large operational scale.
• ~4+ years building LLM-based applications (integrating models, not training).
• 6+ years of development experience with Python, Golang, Java, or similar languages.
• 2+ years of experience building agents (prompt engineering) and developing LLM-based experiences.
• Working experience operating highly available distributed workloads on Kubernetes following a DevOps approach.
• Experience building software for compliance and security in regulated environments is considered an asset.
• A proven track record of architecting and shipping distributed Voice AI or voice platform systems (real-time audio, STT/TTS, telephony or WebRTC) at large operational scale.
• Critically thinking around AI integrations for work processes, decision-making, or problem-solving.
• This may include using AI-powered tools, automating workflows, analysing AI-driven insights, or exploring AI's potential impact on the function or industry.
• Experience building with AI tools such as Claude Code, Cursor, and Windsurf.