Senior AI​/ML Engineer

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.

• 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.

• 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.

• Lead and mentor a team of 2–3 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.
• 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.

• 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, Lang Chain/Llama Index, 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.

• 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.