Head of AI

Head of AI & ML PlatformsFocus: Voice AI, NLP, Conversation Intelligence for Omnichannel Enterprise SalesLocation: Sector 63, Gurugram, Haryana — Full-time, 100% In-Office Work Hours: 10:30 AM – 8:00 PM, Monday to Friday (2nd and 4th Saturdays off) Experience Required: 8–15 years in AI/ML, with 3+ years leading teams in voice, NLP, or conversation platforms Apply: ******* Subject Line: "Application – Head of AI & ML Platforms – (Your Name)"About Darwix AIDarwix AI is a GenAI-powered platform for enterprise revenue teams across sales, support, credit, and retail. Our proprietary AI stack ingests multimodal inputs—voice calls, chat logs, emails, and CCTV streams—and delivers contextual nudges, conversation scoring, and performance analytics in real time.

Our suite of products includes:Transform+: Real-time conversational intelligence for contact centers and field sales

A multilingual GenAI assistant that provides in-the-moment coaching, summaries, and objection handling support

Store Intel: A computer vision solution that transforms CCTV feeds into actionable insights for physical retail spaces

Darwix AI is trusted by large enterprises such as IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar, and Sobha Realty, and is backed by leading institutional and operator investors. We are expanding rapidly across India, the Middle East, and Southeast Asia. Role OverviewWe are seeking a highly experienced and technically strong Head of AI & ML Platforms to architect and lead the end-to-end AI systems powering our voice intelligence, NLP, and GenAI solutions.

This is a leadership role that blends research depth with applied engineering execution. The ideal candidate will have deep experience in building and deploying voice-to-text pipelines, multilingual NLP systems, and production-grade inference workflows. The individual will be responsible for model design, accuracy benchmarking, latency optimization, infrastructure orchestration, and integration across our product suite.

This is a critical leadership role with direct influence over product velocity, enterprise client outcomes, and future platform scalability. Key ResponsibilitiesVoice-to-Text (ASR) ArchitectureLead the design and optimization of large-scale automatic speech recognition (ASR) pipelines using open-source and commercial frameworks (e.g., WhisperX, Deepgram, AWS Transcribe)Enhance speaker diarization, custom vocabulary accuracy, and latency performance for real-time streaming scenarios

Build fallback ASR workflows for offline and batch mode processing

Implement multilingual and domain-specific tuning, especially for Indian and GCC languages

Natural Language Processing and Conversation AnalysisBuild NLP models for conversation segmentation, intent detection, tone/sentiment analysis, and call scoring

Implement multilingual support (Hindi, Arabic, Tamil, etc.) with fallback strategies for mixed-language and dialectal inputs

Develop robust algorithms for real-time classification of sales behaviors (e.g., probing, pitching, objection handling)Train and fine-tune transformer-based models (e.g., BERT, RoBERTa, DeBERTa) and sentence embedding models for text analyticsGenAI and LLM IntegrationDesign modular GenAI pipelines for nudging, summarization, and response generation using tools like LangChain, LlamaIndex, and OpenAI APIsImplement retrieval-augmented generation (RAG) architectures for contextual, accurate, and hallucination-resistant outputs

Build prompt orchestration frameworks that support real-time sales coaching across channels

Ensure safety, reliability, and performance of LLM-driven outputs across use cases

Infrastructure and DeploymentLead the development of scalable, secure, and low-latency AI services deployed via FastAPI, TorchServe, or similar frameworks

Oversee model versioning, monitoring, and retraining workflows using MLflow, DVC, or other MLOps tools

Build hybrid inference systems for batch, real-time, and edge scenarios depending on product usage

Optimize inference pipelines for GPU/CPU balance, resource scheduling, and runtime efficiency

Team Leadership and Cross-functional CollaborationRecruit, manage, and mentor a team of machine learning engineers and research scientists

Collaborate closely with Product, Engineering, and Customer Success to translate product requirements into AI features

Own AI roadmap planning, sprint delivery, and KPI measurement

Serve as the subject-matter expert for AI-related client discussions, sales demos, and enterprise implementation roadmaps

Required Qualifications8+ years of experience in AI/ML with a minimum of 3 years in voice AI, NLP, or conversational platforms

Proven experience delivering production-grade ASR or NLP systems at scale

Deep familiarity with Python, PyTorch, HuggingFace, FastAPI, and containerized environments (Docker/Kubernetes)Expertise in fine-tuning LLMs and building multi-language, multi-modal intelligence stacks

Demonstrated experience with tools such as WhisperX, Deepgram, Azure Speech, LangChain, MLflow, or Triton Inference ServerExperience deploying real-time or near real-time inference models at enterprise scale

Strong architectural thinking with the ability to design modular, reusable, and scalable ML services

Track record of building and leading high-performing ML teams

Preferred SkillsBackground in telecom, contact center AI, conversational analytics, or field sales optimization

Familiarity with GPU deployment, model quantization, and inference optimization

Experience with low-resource languages and multilingual data augmentation

Understanding of sales enablement workflows and domain-specific ontology development

Experience integrating AI models into customer-facing SaaS dashboards and APIsSuccess MetricsTranscription accuracy improvement by ≥15% across core languages within 6 months

End-to-end voice-to-nudge latency reduced below 5 secondsGenAI assistant adoption across 70%+ of eligible conversationsAI-driven call scoring rolled out across 100% of Tier 1 clients within 9 months

Model deployment velocity (dev to prod) reduced by ≥40% through tooling and process improvements

Culture at Darwix AIAt Darwix AI, we operate at the intersection of engineering velocity and product clarity. We move fast, prioritize outcomes over optics, and expect leaders to drive hands-on impact. You will work directly with the founding team and senior leaders across engineering, product, and GTM functions.Expect ownership, direct communication, and a culture that values builders who scale systems, people, and strategy.Compensation and BenefitsCompetitive fixed compensation

Performance-based bonuses and growth-linked incentivesESOP eligibility for leadership candidates

Access to GPU/compute credits and model experimentation infrastructure

Comprehensive medical insurance and wellness programs

Dedicated learning and development budget for technical and leadership upskillingMacBook Pro, premium workstation, and access to industry tooling licenses

Career Progression12-month roadmap: Build and stabilize AI platform across all product lines18–24-month horizon: Elevate to VP of AI or Chief AI Officer as platform scale increases globally

Future leadership role in enabling new verticals (e.g., healthcare, finance, logistics) with domain-specific GenAI solutions

How to ApplySend the following to ******* CV (PDF format)A short statement (200 words max) on: "How would you design a multilingual voice-to-text pipeline optimized for low-resource Indic languages, with real-time nudge delivery?"Links to any relevant GitHub repos, publications, or deployed projects (optional)Subject Line: "Application – Head of AI & ML Platforms – (Your Name)"