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Sr. Machine Learning Engineer

6 hours, 38 minutes ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
AWS CI/CD Computer Vision Docker DynamoDB Machine Learning Matplotlib MongoDB OpenCV Pandas Pillow Python PyTorch SageMaker Scikit-learn TensorFlow
Apply Now
Mitek Systems

Mitek Systems

Mitek Systems develops and provides mobile capture and identity verification software solutions that enable enterprises to securely verify user identities and facilitate transactions through mobile devices, enhancing customer experiences while preventi...

Communications Equipment
251-1K
Founded 1985
View All Jobs 9

Description

  • Build, train, and optimize computer vision models for image classification, face liveness detection, and presentation attack detection (PAD) / anti-spoofing.
  • Develop ML solutions for biometric identity verification, fraud detection, replay attacks, deepfakes, and synthetic media threats.
  • Design and run experiments to improve model accuracy, recall, robustness, and fraud detection performance.
  • Train and tune deep learning models such as CNNs, Vision Transformers, and foundation models on large-scale image datasets.
  • Prepare and curate noisy datasets through ingestion, validation, cleaning, deduplication, labeling, and dataset QA.
  • Develop evaluation protocols and metrics that account for fraud detection effectiveness, false acceptance rates, false rejection rates, and business impact.
  • Build production-grade training and inference pipelines on AWS with reproducibility, monitoring, observability, and cost controls.
  • Productionize models as resilient Python services and libraries and work with platform teams on APIs, latency, scalability, and reliability.
  • Partner with Product, Customer Success, Fraud, and Platform Engineering teams to meet privacy, compliance, security, and reliability requirements.
  • Mentor other engineers through design reviews, code reviews, experimentation best practices, and knowledge sharing.

Requirements

  • Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent professional experience.
  • 5+ years of experience in applied machine learning, computer vision, or ML engineering with strong software engineering fundamentals, or an equivalent combination of education and experience.
  • Strong Python programming skills and experience building production-quality machine learning systems.
  • Experience developing and deploying computer vision models for image classification, detection, segmentation, or related image-based learning tasks in production.
  • Hands-on experience designing, training, evaluating, and optimizing deep learning models using PyTorch or TensorFlow.
  • Strong computer vision background, including experience with CNNs, Vision Transformers, foundation models, image processing, and feature extraction techniques.
  • Experience working with large-scale image datasets, including 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 real-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 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 Docker, CI/CD, monitoring, model/version management, and end-to-end troubleshooting.
  • Experience optimizing models for real-time constraints using 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 related fraud detection systems is strongly preferred.
  • Experience working with face-based systems, biometric image data, or adversarial computer vision problems is a strong plus.
  • Experience with synthetic data generation, domain adaptation, data augmentation, or techniques for improving model robustness and generalization in real-world environments.

Benefits

  • $150,000 - $185,000 annual salary range.
  • Universal, supplemental, and private healthcare plan choices based on country specifics.
  • Retirement or pension plan contributions and MTK stock plan participation.
  • Life event and disability coverage.
  • Generous annual leave, company holidays, and volunteer time off.
  • E-learning license, tuition reimbursement, and hackathons.
  • Home office setup allowance.
  • Optional benefits including pet insurance, identity theft protection, and legal assistance.

Interested in this position?

Apply directly on the company website

Apply Now

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