Sr. Machine Learning Engineer

Mitek Systems

12d • Remote

About The Position

As a Sr. Machine Learning Engineer, you will lead applied ML initiatives that power our next-generation Identity Verification (IDV) engine. You'll work hands-on across the full lifecycle - data collection, organization, model design, training, evaluation, and production monitoring - delivering models that are accurate, fast, and cost-efficient in real-world, adversarial environments.
Advancement Opportunities:
We are targeting Sr. Machine Learning Engineers who have a passion for coaching, mentoring and growing team members. This role will start as an individual contributor and offer the opportunity to move into a player/coach leader within the first year of employment.

About Mitek Systems:
Specializing in identity verification, authentication, biometrics, image capture, and fraud detection, our products ensure swift onboarding, instant identity verification, and robust defense against rising threats, such as check fraud, deepfakes, and AI-powered fraud. Trusted by millions globally, our enterprise-grade solutions are relied on by some of the world's leading enterprises, offering peace of mind for both the company and their customers. Our mission is simple but essential: To protect what's real.

Requirements

• Bachelors degree in computer science or related field (or equivalent professional experience)
• Knowledge, skills and abilities typically gained from 5+ years of experience in applied machine learning / ML engineering with strong software engineering fundamentals (or equivalent combination of education and experience).
• Strong Python skills and experience building production ready code.
• Demonstrated experience solving computer vision tasks with ML models utilizing PyTorch or Tensorflow.
• Strong computer vision background, including experience with CNNs, vision transformers, and foundation models.
• Proven ability to work with large datasets and build reliable data preprocessing/feature engineering pipelines; comfort with distributed data tooling is a plus.
• Clear communication skills and the ability to work effectively across engineering, product, and operations stakeholders.

Nice To Haves

• Experience running ML in production: containerization (Docker), CI/CD, monitoring, and model/version management; ability to troubleshoot data/model issues end-to-end.
• Experience optimizing models for real-time constraints (quantization, distillation, pruning, ONNX) and performance tuning for CPU/GPU inference.
• Model understanding / interpretability experience (e.g., Grad-CAM, saliency maps, error slicing, and targeted evaluation).
• Experience with experiment tracking (e.g., MLflow, Weights & Biases) and strong habits around reproducibility.

Responsibilities

• Build, train, and ship ML models for identity verification use cases such as biometric matching, liveness / anti-spoofing, identity document processing (OCR/extraction), and fraud detection (team assignment based on experience).
• Prepare large, noisy datasets: ingestion, validation, cleaning, deduplication, labeling strategy, and dataset QA to improve model performance and reliability.
• Design experiments, evaluation protocols, and success metrics (offline and online), iterate based on measurable business impact (detection rates, fraud losses, false positives).
• Develop production-grade training and inference pipelines on AWS with strong reproducibility, monitoring, and cost controls.
• Productionize models as resilient services and libraries in Python; collaborate with platform teams on APIs, latency and observability.
• Contribute to the transformation of our IDV engine: modernizing legacy components, improving modularity, and raising quality, performance, and maintainability.
• Work closely with Product, Customer Success, and Platform Engineering teams to ensure ML solutions meet privacy, compliance, and reliability requirements.
• Support other engineers through design reviews, code reviews, and knowledge sharing; help raise the technical bar across the team.

Benefits

• Wellness: Universal, supplemental, and private healthcare 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 251-500 employees