Machine Learning Engineer (Speech & GenAI)

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

AI / ML Engineering

• Design, develop, and deploy AI/ML-powered applications with a focus on:
• Speech-to-text (ASR)
• Text-to-speech (TTS)
• 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.

Cloud & Platform

• 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.

Leadership & Innovation

• 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
• NLP techniques
• Modern AI model architectures, including LLMs
• Proven experience deploying and operating AI workloads on Microsoft Azure.
• Strong engineering fundamentals in:
• System design
• APIs
• Data pipelines
• 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:
• Azure OpenAI
• Azure ML
• LangChain
• MLflow
• PyTorch or TensorFlow
• Exposure to conversational AI, semantic search, sentiment analysis, or intent recognition.

Cloud & Engineering

• Strong experience with Azure services, including:
• Azure OpenAI
• Azure ML
• Azure Functions / Container Apps
• Azure AI Search
• 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

Generative AI / ML, Speech AI (ASR/TTS), Python, Microsoft Azure