Job Description

Accountabilities:

The role focuses on designing, developing, and scaling production-grade computer vision systems while driving technical excellence across machine learning initiatives.

• Lead the architecture, development, and optimization of computer vision solutions focused on biometric applications, including face detection, recognition, quality assessment, and attribute analysis.
• Build, train, evaluate, and improve machine learning models using frameworks such as PyTorch, TensorFlow, and/or JAX.
• Own end-to-end machine learning pipelines, including data ingestion, preparation, training workflows, deployment, and monitoring.
• Design automated data workflows using tools such as Airflow, ensuring high-quality, diverse, and balanced datasets for model development.
• Conduct fairness analysis and benchmarking of biometric models across different datasets and operating conditions to reduce bias and improve reliability.
• Optimize ML models for production environments through techniques such as quantization, distillation, TensorRT, and ONNX.
• Deploy and scale machine learning services using cloud infrastructure, including AWS-based environments.
• Mentor other machine learning engineers, contribute to technical reviews, and promote engineering best practices.
• Collaborate with cross-functional teams to deliver secure, scalable, and high-performing AI solutions.

Requirements:

The ideal candidate brings strong expertise in machine learning, computer vision, and production AI systems, combined with excellent engineering and collaboration skills.

• 5+ years of professional experience in machine learning engineering, including at least 3 years focused on biometrics or face analysis.
• Deep knowledge of computer vision techniques, especially face recognition systems and image-based machine learning applications.
• Strong understanding of algorithmic fairness principles and practical experience identifying and mitigating bias in AI models.
• Advanced Python programming skills with experience using machine learning and computer vision libraries such as OpenCV, Pillow, and PyTorch.
• Proven experience designing complete ML pipelines from data preparation and model training through deployment and production operations.
• Hands-on experience scaling training workloads using multi-GPU environments and deploying ML solutions on AWS services such as SageMaker, EC2, or EKS.
• Experience with workflow orchestration tools such as Airflow and modern ML engineering practices.
• Strong software engineering skills with the ability to write clean, maintainable, and production-ready code.
• Excellent communication skills and the ability to collaborate with technical teams and stakeholders.
• Nice-to-have experience includes research publications in computer vision, vector databases, edge/mobile AI deployment, synthetic data generation, privacy and compliance in biometric systems, or AI-assisted development tools.

Benefits:

• Fully remote work opportunity with flexibility to work from India.
• Opportunity to contribute to advanced AI and computer vision solutions with global impact.
• Work on challenging machine learning problems involving biometrics, fairness, and large-scale production systems.
• Collaborative environment with opportunities to mentor peers and influence technical direction.
• Inclusive workplace that values diverse perspectives, ideas, and professional backgrounds.
• Opportunities for continuous learning and career development within a growing technology organization.
• Competitive compensation package and employee benefits.