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
