AI Engineer (Voice Applications)

Durus Consulting; Chennai District; On-site; INR 400,000 - 750,000; Full time

Benefits offered by this job

Competitive compensation

Cutting-edge Voice AI projects

Career growth opportunities

Job summary

Durus Consulting in Chennai seeks a Staff Engineer / Sr. Manager - AI - Engineer (Voice Applications) to lead architecture and delivery of high-throughput Voice AI systems for speech transcription and real-time translation.

You will mentor engineers, set standards, and partner with cloud infra teams to build production-grade pipelines with MLOps, monitoring, and cost optimization across multilingual audio data.

Qualifications

• M.Tech or PhD in Computer Science, Machine Learning, Computational Linguistics, or a closely related quantitative discipline from a top-tier institution.
• 58 years of hands-on experience in AI/ML engineering with production-grade scale.
• Proven impact designing, deploying, and maintaining multiple high-volume Voice AI systems (STT/NMT).
• Expert in Python and modern Voice AI frameworks; strong knowledge of STT and NMT models (Whisper, Wav2Vec, Transformer).
• Experience with cloud platforms and MLOps tools; strong monitoring and cost optimization capabilities.

Responsibilities

• Lead design and deployment of scalable Voice AI architectures for high-throughput transcription and translation.
• Own end-to-end delivery from ideation to monitoring and iteration.
• Mentor AI/ML engineers; set standards and drive continuous improvement.
• Leverage cloud-native AI services and optimize compute, storage, and networking for real-time workloads.
• Champion MLOps, CI/CD, model versioning, testing, and anomaly detection.
• Collaborate with data scientists, product managers, and stakeholders to align solutions with business needs.
• Stay at the forefront of Speech Recognition, NMT, and large-scale audio processing.

Skills

Python

Voice AI/NLP/Audio

Transformer architectures

Speech-to-Text (STT)

Neural Machine Translation (NMT)

PyTorch

TensorFlow

Hugging Face Transformers

NeMo

Education

M.Tech or PhD in CS/ML/Computational Linguistics

Tools

AWS

Azure

GCP

MLflow

Kubeflow

SageMaker Pipelines

Docker

Kubernetes

Job description

Job Title: Staff Engineer / Sr. Mgr - AI - Engineer (Voice Applications)
Location: Chennai

The Opportunity

We are seeking a seasoned and visionary AI - Engineer to join our core AI/ML team, specifically focused on architecting and leading the development of cutting-edge Voice AI applications. As the AI Lead Engineer for Voice Applications, you will play a pivotal role in designing, developing, and operationalizing advanced AI/ML solutions that directly enable high-accuracy Speech Transcription (STT) and real-time Audio Translation services. This role is ideal for a hands-on technical leader who thrives at the intersection of robust engineering and innovative voice AI research. You will lead the end-to-end design and deployment of scalable, low-latency Voice AI systems, transforming state-of-the-art models (such as Transformer/Attention-based architectures) into robust, production-grade solutions. Your work will directly influence mission-critical operations involving multilingual communication and large-scale audio data processing.

Key Responsibilities

Voice AI System Architecture

• Lead the design and implementation of scalable, secure, and high-performance Voice AI architectures, specifically optimized for high-throughput audio transcription and translation services.
• Define architectural standards and best practices for audio data pipelines, model deployment, and system integration in a voice-centric context.

End-to-End Voice Solution Delivery

• Own the full lifecycle of Voice AI solutionsfrom ideation and prototyping to deployment, monitoring, and continuous improvement.
• Ensure solutions are production-ready, maintainable, and meet stringent requirements for accuracy, latency, and real-time performance across multiple languages and dialects.

Engineering Leadership

• Guide and mentor a team of AI/ML engineers, fostering a culture of technical excellence, innovation, and collaboration. Conduct code reviews, set engineering standards, and drive continuous improvement within the Voice AI practice.

Cloud-Native AI

• Leverage and integrate cloud-native AI/ML services (AWS, GCP, Azure), including specialized Speech and Translation APIs, to accelerate development and ensure scalability.
• Optimize compute, storage, and networking for intensive audio processing and real-time inference workloads.

MLOps & Automation for Voice

• Champion MLOps practices, including CI/CD for ML, model versioning, automated testing, and retraining pipelines.
• Implement robust monitoring for operational reliability and model performance, with specific attention to audio data drift, acoustic quality, and transcription/translation error rates.

Cross-Functional Collaboration

• Partner with data scientists, researchers, product managers, and business stakeholders to translate complex voice requirements into scalable and business-aligned AI/ML solutions.

Innovation & Problem Solving

• Stay ahead of the curve on emerging technologies in Speech Recognition, Neural Machine Translation (NMT), and large-scale audio processing. Identify opportunities to apply novel techniques (e.g., few-shot learning, cross-lingual transfer) to solve high-impact voice-related business problems.

Required Qualifications

Education

• M.Tech or PhD in Computer Science, Machine Learning, Computational Linguistics, or a closely related quantitative discipline from a top-tier institution.

Experience

• Minimum 58 years of hands-on experience in AI/ML engineering, with a proven track record of delivering production-grade solutions at scale.

Proven Impact

• Demonstrated success in designing, deploying, and maintaining multiple high-volume Voice AI systems (STT and/or NMT) in production. Be prepared to discuss the business impact, technical challenges, and your leadership role.

Technical Mastery (Voice Focus)

• Expert-level proficiency in Python and software engineering principles.
• Deep expertise in Voice AI/NLP/Audio frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers, Fairseq, NeMo, or equivalent).
• Strong understanding of modern Speech-to-Text (STT) and Neural Machine Translation (NMT) models (e.g., Whisper, Wav2Vec, Transformer architectures).
• Expertise in working with large audio datasets, acoustic modeling, and language modeling.

Cloud Expertise

• Deep experience with at least one major cloud platform (AWS, Azure, GCP), particularly with AI/ML services, infrastructure automation, and cost optimization.

MLOps Proficiency

• Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker Pipelines). Strong understanding of model lifecycle management and operational monitoring.

Preferred Qualifications

• Experience with real-time audio streaming and processing technologies (e.g., Kafka, gRPC).
• Familiarity with containerization and orchestration (Docker, Kubernetes) for microservices supporting Voice AI.
• Experience with advanced audio preprocessing techniques, noise reduction, and handling various dialects/accents.
• Familiarity with distributed data processing and big data ecosystems for training large models (e.g., Spark, Databricks).

What We Offer

• A leadership role at the forefront of Voice AI innovation, with direct influence on strategic, customer-facing initiatives.
• Access to cutting-edge tools, infrastructure, and large-scale audio datasets to support ambitious Speech and Translation projects.
• A collaborative, high-performance environment that values creativity, autonomy, and continuous learning.
• Competitive compensation and a clear path for career advancement within a rapidly growing AI organization.