Machine Learning Engineer (Speech & GenAI)

Bean HR Consulting; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Bean HR Consulting in Bengaluru, India is looking for a hands-on Staff Engineer – AI/ML (Speech & GenAI) to design, build, and scale production-grade AI systems for real-time speech processing, NLP, and LLM-powered applications in a cloud-native environment.

You will bring deep Python expertise, strong AI/ML experience, and proven deployment of AI workloads on Microsoft Azure, APIs, and scalable backend services, with mentoring across the team.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience in software engineering with significant hands‑on AI/ML work.
• Strong proficiency in Python for building production‑grade AI services.
• Proven experience deploying and operating AI workloads on Microsoft Azure.
• Experience with APIs, scalability, and reliability in backend systems.

Responsibilities

• Design, develop, and deploy AI/ML-powered applications with a focus on speech-to-text, NLP, LLMs, and GenAI.
• Integrate and operationalize speech, language, and GenAI models into scalable backend services.
• Build AI-driven features including real-time voice transcription, intent detection, and Conversational AI.
• Fine-tune models for domain-specific language, accents, and noisy environments; manage ML lifecycle.

Skills

Python

AI/ML

Speech AI

GenAI

Backend APIs

Cloud-native

Education

Bachelor's degree in Computer Science or related field

Tools

Azure

Docker

Kubernetes

MLflow

LangChain

PyTorch

TensorFlow

Job description

Job Description: Staff Engineer – AI / ML (Speech & Generative AI)

Role Summary

We are seeking a hands-on Staff Engineer – AI/ML to design, build, and scale AI-driven speech, voice, and Generative AI solutions. This role focuses on developing production-grade AI systems for real-time speech processing, NLP, and LLM-powered applications in a cloud-native environment.

The ideal candidate has strong Python expertise, deep experience with Speech AI and GenAI, and a proven track record of deploying AI/ML systems on Microsoft Azure.

Key Responsibilities

• Design, develop, and deploy AI/ML-powered applications with a focus on:
• Speech-to-text (ASR)
• Natural Language Processing (NLP)
• Large Language Models (LLMs) and Generative AI
• Integrate and operationalize speech, language, and GenAI models into scalable backend services.
• Build AI-driven features including:
• Real-time voice transcription and speech processing
• Intent detection and entity extraction
• Conversational AI and virtual assistants
• Summarization, semantic search, and RAG-based workflows
• Fine-tune and adapt models for domain-specific language, accents, noisy environments, and real-world usage scenarios.
• Build and maintain cloud-native AI pipelines on Microsoft Azure.
• Deploy, scale, monitor, and optimize AI workloads for performance and cost.
• Implement ML lifecycle management, including model versioning, evaluation, and monitoring.
• Ensure reliability, observability, security, and compliance of AI systems.

Architecture & Collaboration

• Make independent architecture and design trade-off decisions across multiple services.
• Collaborate with backend engineers, product managers, UX designers, and platform teams to deliver end-to-end AI features.
• Participate in design reviews, architecture discussions, and technical documentation.
• Engage in customer or stakeholder discussions to align AI solutions with real-world requirements.
• Mentor junior engineers and contribute to raising overall AI/ML engineering maturity.
• Drive engineering best practices around testing, scalability, and reliability.
• Contribute to innovation through internal IP creation, invention disclosures, or patents.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience in software engineering with significant hands‑on AI/ML work.
• Strong proficiency in Python for building production‑grade AI services.
• Solid understanding of:
• Machine learning fundamentals
• Proven experience deploying and operating AI workloads on Microsoft Azure.
• Strong engineering fundamentals in:
• APIs
• Scalability and reliability

Preferred / Desired Qualifications

AI / ML & Generative AI

• Hands‑on experience with:
• LLMs, prompt engineering, and model evaluation
• Retrieval-Augmented Generation (RAG) architectures
• Experience integrating or fine‑tuning speech models (ASR/TTS) for real‑world applications.
• Familiarity with tools and frameworks such as:
• LangChain
• MLflow
• PyTorch or TensorFlow
• Exposure to conversational AI, semantic search, sentiment analysis, or intent recognition.
• Strong experience with Azure services, including:
• Azure Functions / Container Apps
• Experience with Docker, Kubernetes, CI/CD pipelines, and ML lifecycle management.
• Exposure to AWS or GCP is a plus.
• Background in Java-based backend systems is a plus.
• Experience integrating third‑party APIs and AI services.
• Comfortable working in an Agile development environment.

Preferred Skill Summary