Senior Scientist - Machine Learning

We’re looking for an experienced and hands-on Senior Machine Learning Scientist with deep expertise in audio and speech technologies to drive the design, development, and deployment of advanced ML models powering our data integration platform. In this role, you will focus on speech-to-text (with domain adaptation), speaker identification, keyword spotting, language identification, and deep fake detection. You will work closely with engineering and data infrastructure teams to build, optimize, and deploy scalable ML services in production using NVIDIA Triton, Kubernetes, and modern transformer-based architectures.

Key Responsibilities

• Lead the ML Audio team in developing, training, and deploying production-grade models for:
  • Speech-to-text (including domain adaptation)
  • Speaker identification and verification
  • Keyword spotting
  • Language identification
  • Deepfake and synthetic audio detection
• Research and integrate transformer-based and multi-modal model architectures into production pipelines.
• Collaborate with platform engineers to deploy ML models via NVIDIA Triton Inference Server and ensure low-latency, scalable serving.
• Design and maintain Airflow DAGs for data preprocessing, feature extraction, and model enrichment pipelines.
• Ensure continuous improvement of models through retraining, performance monitoring, and data feedback loops.
• Mentor and guide ML engineers and researchers, fostering a culture of technical rigor, creativity, and collaboration.

Requirements

• Proven experience working within ML teams, ideally in audio/speech technology domains.
• Strong foundation in machine learning and deep learning, particularly in speech processing and audio analysis.
• Hands-on experience with speech-to-text systems (ASR, domain adaptation, fine-tuning large models), speaker recognition, keyword spotting, language ID, and deepfake detection.
• Proficiency in Python and familiarity with C++, Golang, Rust for performance-critical components is beneficial.
• Experience deploying ML models in production using NVIDIA Triton and container orchestration platforms (e.g., Kubernetes).

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Electrical Engineering, or related field (PhD preferred).
• Demonstrated record of leading ML initiatives from research to production.
• Experience in startups or fast-paced, product-centric teams is highly desirable.

Experience

• 5–7 years of combined software engineering and ML experience.
• Proven success delivering speech or audio-based ML models in production environments.

Skills

• Speech-to-Text (ASR) & Domain Adaptation
• Speaker & Keyword Recognition
• Language Identification
• Deepfake Detection
• Transformer & Multimodal Architectures
• NVIDIA Triton Inference Server
• Airflow & ML Pipeline Orchestration
• Kubernetes / Cloud Deployment
• Programming: Python, C++
• MLOps, CI/CD for ML Systems

Location
Abu Dhabi, United Arab Emirates