At SingleInterface, we are redefining how multi-location brands connect with customers in an AI-driven digital world. Backed by $30M in funding from PayPal Ventures and Asia Partners, we are scaling our AI Retail Tech Platform to empower businesses with seamless digital presence management, AI-powered customer engagement, online reputation management, and store-level product & service integration. Our data-driven approach helps brands enhance customer experience, gain insights, and drive revenue growth.
Our Vision
Making AI-driven solutions simple & accessible for hyperlocal businesses to manage complex digital marketing needs.
Our Goal
Fuel growth for 10 million business locations by 2030 through advanced AI-powered frictionless experiences.
Our Core Values
- Customer First – We put our customers at the heart of everything we do.
- Getting Things Done – Speed and execution define our approach.
- Being Authentic – We stay true to our people and mission.
- Being Finicky – We obsess over the details that matter.
- Being Techurious – We challenge the status quo with tech-driven solutions.
About the Role
We are hiring a Senior AI Engineer, Voice AI to build state-of-the-art voice AI systems for real-world customer conversations. The ideal candidate has deep experience across speech and language layers, including ASR, dualization, multilingual voice pipelines, LLM prompting and optimization, summarization, extraction, and low-latency production deployment.
This is not a pure integration role. We are looking for someone who can operate close to the model and systems layer, make strong architectural trade-offs, and build reliable conversational AI under real-world constraints such as noisy telephony audio, multilingual users, interruptions, latency sensitivity, and business-critical workflows.
You will work on production voice agents and conversational intelligence systems that power customer interactions at scale, across live conversations, post-call analytics, and automation workflows.
Key Responsibilities
- Design, build, and improve real-time Voice AI systems for customer conversations.
- Develop and optimize systems across the voice stack, including:
- Automatic speech recognition (ASR)
- Speaker diarization
- Voice activity detection (VAD)
- language identification
- LLM reasoning and orchestration
- response generation
- text-to-speech (TTS)
- interruption handling and turn-taking
- Build low-latency, production-grade inference pipelines for live voice interactions.
- Improve multilingual and code-switched conversational performance for real-world telephony environments.
- Design prompt workflows, structured outputs, tool usage, and fallback logic to improve accuracy, control, and resolution rates.
- Build and refine systems for:
- summarization
- information extraction
- classification
- sentiment and emotion analysis
- call dispositioning
- topic and intent detection
- quality monitoring
- Define and implement evaluation frameworks for conversational quality, latency, hallucination, containment, task completion, extraction accuracy, and business outcomes.
- Fine-tune and optimize LLMs and speech models for domain-specific performance where needed.
- Work closely with product, engineering, and operations teams to translate ambiguous business problems into scalable AI systems.
- Troubleshoot production failures across speech, orchestration, and model behaviour, and drive measurable improvements.
Required Qualifications
- 5+ years of experience in AI/ML/NLP, with strong hands-on experience in Voice AI, Speech AI, or Conversational AI.
- Proven experience building or improving production voice systems used in real customer interactions.
- Strong understanding of the speech pipeline, including one or more of:
- ASR
- diarization
- VAD
- language identification
- TTS
- telephony audio handling
- Strong experience with LLMs in production, including prompting, orchestration, evaluation, summarization, extraction, or agent workflows.
- Strong programming skills in Python and experience with frameworks such as PyTorch, TensorFlow, or similar.
- Experience with model serving, inference optimization, and production performance tuning.
- Strong grasp of system design trade-offs across latency, quality, reliability, and cost.
- Ability to work hands-on across experimentation, shipping, debugging, and iterative improvement.
Preferred Qualifications
- Experience working in contact center AI, conversational analytics, or enterprise customer interaction products.
- Experience with multilingual speech systems, especially for Indian or other non-English language environments.
- Familiarity with tools, frameworks, or models such as:
- Whisper
- Kaldi
- Hugging Face
- streaming ASR pipelines
- neural TTS systems
- Experience with:
- prompt optimization
- fine-tuning
- PEFT / LoRA
- distillation
- evaluation harnesses
- structured generation
- Experience designing systems for:
- call summarization
- QA automation
- compliance monitoring
- agent assist
- sentiment/emotion detection
- conversation intelligence
- Familiarity with production infrastructure such as Docker, Kubernetes, Redis, message queues, observability tooling, and scalable API services
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