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Senior AI Engineer

Senior AI Engineer

Bajaj Finance

2 - 7 years

9 - 13 Lacs

pune

Posted:1 day ago| Platform:

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Skills Required

ai engineer python natural language processing ai llm machine learning privacy compliance data collection ai deployment research r tensorflow nlp cloud architecture apis compliance pytorch data privacy ml engineer architecture

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Purpose

We are seeking a dynamic AI/ML Engineer to join our pioneering voice Gen AI RD team. The ideal candidate will possess a strong foundation in machine learning and a passion for innovation. This role involves developing advanced voice AI solutions.

Duties and Responsibilities

Research and Innovation: Stay abreast of the latest advancements in Gen AI/ML technologies, contributing to research initiatives and applying innovative solutions to practical problems

Generative AI Model Optimization:

Fine-tune LLMs/SLMs with proprietary NBFC data

Perform distillation, quantization of LLMs for edge deployment

Evaluate and run LLM/SLM models on local/edge server machines

Conversational Intelligence:

Develop and fine-tune BOTs capable of negotiation using contextual understanding, emotion detection, and dynamic loan pitch logic

Build intelligent Dialogue Management frameworks that adapt in real-time

Speech Technology RD:

Evaluate Speech-to-Speech (S2S) models for natural voice responses

Assess STT models for indic dialects accuracy; explore emotion-aware TTS engines

Experiment with speaker diarization for multi-speaker environments

Voice Biometrics Security:

Collect and analyze voice samples for biometric model training

Evaluate biometric algorithms for fraud prevention and authentication

Implement anti-spoofing techniques to prevent deepfakes/recorded attacks

Ensure data privacy compliance in voice data usage

Self-Learning Frameworks:

Build self-learning systems that adapt without full retraining (e.g., learn new rejection patterns from calls)

Implement lightweight local models to enable real-time learning on the edge.

Key Decisions / Dimensions

Model Selection Customization

Choosing the right STT, TTS, and S2S models for various Indic languages and dialects

Deciding between open-source vs. commercial APIs based on latency, cost, and control

LLM/SLM Strategy

Selecting appropriate LLM/SLM architectures for dialogue management and negotiation logic

Deciding what to fine-tune, distill, or quantize, and what to leave generic

Edge vs. Cloud Architecture

Making trade-offs between on-device processing and cloud-based orchestration

Defining what runs locally for speed/privacy and what needs backend support

Emotion Dialogue Logic Integration

Mapping emotional cues to appropriate TTS responses and negotiation tone

Designing fallback logic for unrecognized or hostile user responses

Voice Biometrics Algorithm Evaluation

Choosing and testing biometric algorithms for authentication and anti-spoofing

Deciding thresholds for matching, rejection, and fraud escalation.

Major Challenges

Building a bot that doesn''t just answer but negotiates with human-like reasoning

Running large models (LLM/STT/TTS) in low-latency, low-bandwidth environments without cloud dependency

Understanding caller emotions in noisy, multilingual conditions (anger, hesitation, sarcasm)

Ensuring STT and TTS pipelines work well with dialect-rich, low-resource Indian languages

Preventing fraud via recorded calls or deepfake voices

Bot must learn from failed interactions

Required Qualifications and Experience

Educational Background: Bachelors or Masters degree in Computer Science, Engineering, or a related field

Experience: 28 years of experience in AI/ML, with exposure to Natural Language Processing (NLP) and speech technologies

Strong experience in Speech AI STT, TTS, S2S, speaker diarization, or related areas

Proficiency in LLMs/SLMs, Hugging Face, LangChain, or OpenAI stack

Experience with model optimization techniques (quantization, distillation)

Knowledge of edge AI deployment, low-latency serving

Understanding of emotion modeling, biometric systems, and anti-spoofing

Experience in Python, PyTorch/TensorFlow, and scalable deployment workflows

Bonus: Experience in Indian language dialects, voice data collection, or field deployments in semi-urban/rural settings

a)LLM Finetuning, Speech AI STT, TTS, S2S, speaker diarization

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Senior AI Engineer