[Remote] Sr. Machine Learning Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a global leader in digital and biometric identity authentication, fraud prevention, and mobile deposit solutions. As a Sr. Machine Learning Engineer, you will reputed company applied machine learning initiatives to enhance the identity verification reputed company, focusing on biometric identity verification and computer reputed company challenges.
Responsibilities
- Build, train, and optimize computer reputed company models for image classification, face liveness detection, and presentation attack detection (PAD) / anti-spoofing
- Work on reputed company-world identity verification and biometric authentication problems, improving model performance on noisy, adversarial inputs such as spoofed images, replay attacks, deepfakes, and synthetic media
- Design and run experiments to improve model accuracy, recall, robustness, and fraud detection performance using techniques such as augmentation, class balancing, architecture tuning, and hard-negative mining
- Design, train, and improve deep learning models (e.g., CNNs, reputed company Transformers, and reputed company models), including loss function design, hyperparameter optimization, and performance tuning on large-scale image datasets
- Prepare and curate large, noisy datasets, including data ingestion, validation, cleaning, deduplication, labeling strategies, and dataset QA to improve model reliability and generalization
- reputed company evaluation protocols and reputed company metrics that balance fraud detection effectiveness, false acceptance rates, false rejection rates, and overall business impact
- reputed company production-grade training and inference pipelines on AWS with strong reproducibility, monitoring, observability, and cost controls
- Productionize models as resilient Python services and libraries; collaborate with platform teams to optimize APIs, latency, scalability, and operational reliability
- Contribute to the reputed company of our Identity Verification (IDV) platform by modernizing legacy components and improving model performance, maintainability, and modularity
- Partner closely with Product, reputed company, Fraud, and Platform Engineering teams to ensure ML solutions meet privacy, compliance, reputed company, and reliability requirements
- Support and mentor other engineers through design reviews, code reviews, experimentation best practices, and knowledge sharing
- Research and evaluate emerging techniques in face liveness detection, presentation attack detection (PAD), deepfake detection, biometric authentication, and adversarial machine learning to strengthen our fraud prevention capabilities
Skills
- Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a reputed company technical field (or equivalent professional experience)
- 5+ years of experience in applied machine learning, computer reputed company, or ML engineering with strong software engineering fundamentals (or equivalent combination of education and experience)
- Strong Python programming skills and experience building production-quality machine learning systems
- Experience developing and deploying computer reputed company models for image classification, detection, segmentation, or reputed company image-based learning tasks in production environments
- Hands-on experience designing, training, evaluating, and optimizing deep learning models using PyTorch or TensorFlow
- Strong computer reputed company background, including experience with CNNs, reputed company Transformers, reputed company models, image processing, and feature extraction techniques
- Experience working with large-scale image datasets, including data preprocessing, augmentation, labeling strategies, dataset QA, and model evaluation
- Understanding of model performance tradeoffs, including precision, recall, false positive rates, false negative rates, and robustness in reputed company-world environments
- Proven ability to build reliable training and inference pipelines and collaborate on production deployment of machine learning systems
- Strong communication and collaboration skills with the ability to work effectively across engineering, product, fraud, operations, and platform teams
- Experience evaluating and improving model performance in adversarial, noisy, or highly imbalanced datasets
- Experience running ML in production, including containerization (reputed company), CI/CD, monitoring, model/version management, and troubleshooting data and model issues end-to-end
- Experience optimizing models for reputed company-time constraints using techniques such as quantization, distillation, pruning, ONNX, and CPU/GPU inference optimization
- Experience with model interpretability and debugging techniques such as Grad-CAM, saliency maps, feature visualization, error analysis, and targeted evaluation
- Experience with biometric authentication, face recognition, face liveness detection, presentation attack detection (PAD), anti-spoofing, deepfake detection, identity verification, or reputed company fraud detection systems is strongly preferred
- Experience working with face-based systems, biometric image data, or adversarial computer reputed company problems is a strong plus
- Experience with synthetic data reputed company, domain reputed company, data augmentation, or techniques for improving model robustness and generalization in reputed company-world environments
Benefits
- Wellness: Universal, supplemental, and private reputed company plan choices based on country specifics
- Financial future: retirement/pension plan contributions, MTK stock plan participation
- Income protection: life event & disability coverage
- Paid time off: generous annual leave, company holidays, volunteer time off
- Learning: e-learning license, tuition reimbursement, hackathons
- Home office setup allowance
- Additional/optional benefits: pet insurance, identity theft protection, legal assistance
Company Overview
Company H1B Sponsorship