About the Role
We are building the next generation of AI-powered products from AI receptionists and call intelligence to medical scribes and workflow automation. As our Senior AI/ML Engineer, you will be the technical backbone of our AI function: defining architecture, evaluating and integrating cutting-edge tools and models, and leading a small team of junior engineers to deliver reliable, scalable AI systems in production.
This is a high-ownership role for someone who thrives at the intersection of research and real-world product engineering.
What You'll Do
Technical Leadership
- Evaluate and select AI/ML tools, frameworks, models, and infrastructure best suited for products like AI receptionists, call intelligence, and AI scribes
- Design end-to-end AI system architectures covering speech, LLMs, RAG pipelines, real-time inference, and data workflows
- Define engineering standards, best practices, and code review processes for the AI team
- Make key build-vs-buy decisions and vendor evaluations for AI services and APIs
Product Delivery
- Own the AI layer of our core products from prototyping and experimentation to production deployment
- Stabilise and improve existing AI features: reduce latency, increase accuracy, and improve robustness
- Collaborate with product managers and founders to translate business requirements into AI system design
- Set up monitoring, alerting, and evaluation pipelines to track model and system performance in production
Team Management
- Lead and mentor a team of 23 junior AI/ML engineers through code reviews, pair programming, and technical guidance
- Break down complex AI problems into well-scoped tasks and delegate effectively
- Create a culture of experimentation, rigour, and continuous learning within the team
Research & Innovation
- Stay current with the latest developments in LLMs, speech AI, and agentic systems
- Identify opportunities to leverage new models or techniques to improve product capabilities
- Run structured experiments and present findings to inform product and engineering decisions
What We're Looking For
Required
- 4+ years of experience in AI/ML engineering, with at least 2 years in production environments
- Hands-on experience building systems using LLMs (OpenAI, Anthropic, Gemini, or open-source models)
- Strong proficiency in Python and ML frameworks (PyTorch, Hugging Face, LangChain/LlamaIndex, etc.)
- Experience with speech and audio AI: ASR (e.g. Whisper, Deepgram), TTS, or orchestration platforms (Vapi, Livekit, Retell)
- Solid understanding of RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and prompt engineering
- Experience deploying and scaling AI systems on cloud infrastructure (AWS, GCP, or Azure)
- Track record of leading technical initiatives and mentoring junior engineers
- Strong communication skills able to articulate technical trade-offs to non-technical stakeholders
Nice to Have
- Experience with real-time AI systems (low-latency speech, streaming inference)
- Familiarity with healthcare or medical documentation workflows (for AI scribe use cases)
- Experience with telephony or VoIP platforms (Twilio, Vonage, Plivo)
- Knowledge of multi-agent frameworks and agentic AI workflows
- Prior experience at a startup or in a 0-to-1 product environment
