Senior Data Scientist

JOB DESCRIPTION

Senior Data Scientist

Speech, Voice & Conversational AI

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Department:

Data Science & AI

Experience

12 – 15 Years

Role Overview

We are seeking a highly experienced Senior Data Scientist – Speech, Voice & Conversational AI to lead the architecture, design, and delivery of next-generation voice and speech AI solutions. This role sits at the intersection of deep machine learning expertise and practical product engineering, driving end-to-end voice AI capabilities across Firstsource’s service lines.

The ideal candidate brings 12–15 years of progressive experience in data science with a strong specialization in speech and voice technologies, along with hands-on expertise in Generative AI, Agentic AI frameworks, and modern voice pipeline tooling. You will act as a technical thought leader, shaping our voice AI strategy, mentoring teams, and collaborating with cross-functional stakeholders to deliver production-grade solutions at scale.

Key Responsibilities

Voice & Speech AI Architecture

• Design and own the end-to-end architecture for voice AI solutions including real-time speech-to-text (STT), text-to-speech (TTS), voice-to-voice, speaker diarization, emotion detection, and voice biometrics.
• Evaluate, benchmark, and integrate leading speech platforms and APIs such as Google Cloud Speech, Amazon Transcribe, Azure Speech Services, Whisper (OpenAI), Deepgram, AssemblyAI, ElevenLabs, and PlayHT.
• Build robust voice pipelines that handle noise cancellation, language identification, accent adaptation, and real-time streaming at production scale.

Generative AI & Agentic AI

• Architect and deploy GenAI-powered conversational agents leveraging Large Language Models (LLMs) such as GPT-4, Claude, Gemini, and open-source alternatives (LLaMA, Mistral).
• Design Agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and Semantic Kernel to build multi-step, tool-using voice agents.
• Implement Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate, Qdrant, Chroma) for context-aware voice assistants.
• Drive prompt engineering strategies and fine-tuning approaches (LoRA, QLoRA, RLHF) to optimize LLM performance for speech-centric use cases.

Solution Design & Delivery

• Lead solution design workshops with clients and internal stakeholders to translate business requirements into scalable voice AI architectures.
• Define technical roadmaps, establish best practices, and create reusable solution accelerators for voice and conversational AI.
• Own proof-of-concept (POC) development through to production deployment, working closely with MLOps and engineering teams.

Leadership & Mentoring

• Mentor and upskill a team of data scientists and ML engineers on speech AI and GenAI best practices.
• Represent Firstsource as a subject-matter expert in voice AI at internal reviews, client presentations, and industry forums.
• Stay current on rapidly evolving GenAI, speech, and agentic AI research and translate insights into actionable opportunities.

Technical Skills & Tooling

Domain

Required Proficiency

• Speech-to-Text (STT)
• Whisper, Google Cloud Speech, Azure Speech, Amazon Transcribe, Deepgram, AssemblyAI, Kaldi
• Text-to-Speech (TTS)
• ElevenLabs, PlayHT, Azure Neural TTS, Amazon Polly, Google WaveNet, Tortoise TTS, Bark
• Voice-to-Voice
• Real-time duplex pipelines, WebRTC integration, voice cloning, prosody transfer, streaming architectures
• LLM & GenAI
• GPT-4/4o, Claude, Gemini, LLaMA, Mistral, fine-tuning (LoRA/QLoRA), RLHF, prompt engineering
• Agentic AI Frameworks
• LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, function calling, tool-use patterns
• RAG & Vector DBs
• Pinecone, Weaviate, Qdrant, Chroma, FAISS, embedding models, hybrid search
• ML / Deep Learning
• PyTorch, TensorFlow, Transformers (HuggingFace), audio feature engineering (MFCCs, spectrograms)
• Cloud & MLOps
• AWS / Azure / GCP, Docker, Kubernetes, MLflow, model serving (Triton, TorchServe, vLLM)
• Programming
• Python (advanced), SQL, familiarity with Rust/C++ for performance-critical audio processing
• Telephony & Contact Center
• Twilio, Genesys, Amazon Connect, SIP/VoIP protocols, CCAI (Google Contact Center AI)

Qualifications & Experience

• 12–15 years of progressive experience in Data Science, Machine Learning, or AI Engineering, with at least 5 years focused on speech, voice, or audio ML