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3.0 - 5.0 years
0 Lacs
Pune, Maharashtra, India
On-site
Company Size Large-scale / Global Experience Required 3 - 5 years Working Days 6 days/week Office Location Viman Nagar, Pune Role & Responsibilities Agentic AI Development: Design and develop multi-agent conversational frameworks with adaptive decision-making capabilities. Integrate goal-oriented reasoning and memory components into agents using transformer-based architectures. Build negotiation-capable bots with real-time context adaptation and recursive feedback processing. Generative AI & Model Optimization: Fine-t une LLMs/SLMs using proprietary and domain-specific datasets (NBFC, Financial Services, etc.). Apply distillation and quantization for efficient deployment on edge devices. Benchmark LLM/SLM performance on server vs. edge environments for real-time use cases. Speech And Conversational Intelligence: Implement contextual dialogue flows using speech inputs with emotion and intent tracking. Evaluate and deploy advanced Speech-to-Speech (S2S) models for naturalistic voice responses. Work on real-time speaker diarization and multi-turn, multi-party conversation tracking. Voice Biometrics & AI Security: Train and evaluate voice biometric models for secure identity verification. Implement anti-spoofing layers to detect deepfakes, replay attacks, and signal tampering. Ensure compliance with voice data privacy and ethical AI guidelines. Self-Learning & Autonomous Adaptation: Develop frameworks for agents to self-correct and adapt using feedback loops without full retraining. Enable low-footprint learning systems on-device to support personalization on the edge. Ideal Candidate Educational Qualifications: Bachelors/Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience Required: 35 years of experience, with a mix of core software development and AI/ML model engineering. Proven hands-on work with Conversational AI, Generative AI, or Multi-Agent Systems. Technical Proficiency: Strong programming in Python, TensorFlow/PyTorch, and model APIs (Hugging Face, LangChain, OpenAI, etc.). Expertise in STT, TTS, S2S, speaker diarization, and speech emotion recognition. LLM fine-tuning, model optimization (quantization, distillation), RAG pipelines. Understanding of agentic frameworks, cognitive architectures, or belief-desire-intention (BDI) models. Familiarity with Edge AI deployment, low-latency model serving, and privacy-compliant data pipelines. Desirable: Exposure to agent-based simulation, reinforcement learning, or behavioralmodeling. Publications, patents, or open-source contributions in conversational AI or GenAI systems. Perks, Benefits and Work Culture Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of Indias most diversified Non-banking financial companies, and among Asias top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations were present in India. Skills: edge ai deployment,adaptation,speech emotion recognition,llm fine-tuning,tensorflow,models,intelligence,model optimization,speech,speech-to-speech,data,openai,hugging face,llm,optimization,agents,langchain,pytorch,python Show more Show less
Posted 3 days ago
5.0 - 9.0 years
0 Lacs
hyderabad, telangana
On-site
We are looking for a highly experienced Voice AI /ML Engineer to take the lead in designing and deploying real-time voice intelligence systems. This position specifically involves working on ASR, TTS, speaker diarization, wake word detection, and developing production-grade modular audio processing pipelines to support next-generation contact center solutions, intelligent voice agents, and high-quality audio systems. You will be operating at the convergence of deep learning, streaming infrastructure, and speech/NLP technology, with a focus on creating scalable, low-latency systems that cater to diverse audio formats and real-world applications. Your responsibilities will include: - Building, fine-tuning, and deploying ASR models such as Whisper, wav2vec2.0, and Conformer for real-time transcription. - Developing high-quality TTS systems using VITS, Tacotron, FastSpeech for natural-sounding voice generation. - Implementing speaker diarization to segment and identify speakers in multi-party conversations using embeddings and clustering techniques. - Designing wake word detection models with ultra-low latency and high accuracy even in noisy conditions. In addition to the above, you will also be involved in: - Architecting bi-directional real-time audio streaming pipelines utilizing WebSocket, gRPC, Twilio Media Streams, or WebRTC. - Integrating voice AI models into live voice agent solutions, IVR automation, and AI contact center platforms. - Building scalable microservices for audio processing, encoding, and streaming across various codecs and containers. - Leveraging deep learning and NLP techniques for speech and language tasks. Furthermore, you will be responsible for: - Developing reusable modules for different voice tasks and system components. - Designing APIs and interfaces for orchestrating voice tasks across multi-stage pipelines. - Writing efficient Python code, optimizing models for real-time inference, and deploying them on cloud platforms. Join us to be part of impactful work, tremendous growth opportunities, and an innovative environment at Tanla, where diversity is championed and inclusivity is valued.,
Posted 6 days ago
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