Senior Machine Learning Engineer (Voice Biometrics)

Quick Facts

Role: Senior Machine Learning Engineer (Voice Biometrics)
Work mode: 100% remote
Focus: Speaker verification/identification, anti-spoofing, real-time risk analysis for contact centers
Core stack: Python, AWS (Kinesis, Fargate, SageMaker), TensorFlow/PyTorch, Docker, CI/CD

Description

Work on voice biometrics solutions used for user authentication and fraud prevention in contact centers. You will design, develop, and optimize speaker verification and identification systems, embedding/scoring pipelines, and anti-spoofing and liveness detection. You’ll deploy and maintain production ML systems on AWS with continuous monitoring and performance optimization for real-world audio conditions.

Responsibilities

• Design, develop, and optimize speaker verification and speaker identification solutions
• Develop embedding extraction, enrolment, scoring, calibration, and threshold optimization processes
• Analyze audio quality and optimize models for noise, codecs, and different devices
• Implement anti-spoofing and liveness detection solutions
• Deploy and maintain production machine learning systems in AWS
• Build and develop data pipelines using Amazon Kinesis
• Deploy models using AWS Fargate and SageMaker Endpoints
• Improve monitoring, observability, and system performance
• Participate in code reviews, pair programming, and share knowledge with the team

Benefits

• 100% remote model
• B2B rate: 170 PLN/hour (depending on experience)

Requirements

• 4–5 years of commercial experience in machine learning projects related to voice biometrics
• Practical experience with speaker verification and speaker identification
• Knowledge of embeddings, scoring, calibration, enrolment, and anti-spoofing
• Practical experience with Python and TensorFlow and/or PyTorch
• Hands-on AWS experience, especially Kinesis and Fargate and/or SageMaker
• Knowledge of MLOps, monitoring, deployment, and maintenance of production models
• Good knowledge of SQL, Git, Docker, and CI/CD environments
• Ability to work with existing systems and develop production solutions
• Team collaboration skills, including code review and knowledge sharing
• English at least C1