Machine Learning Engineer

Mitek Systems

4d • Remote

About The Position

As a Machine Learning Engineer, you will participate in 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.

Requirements

• Bachelors degree in computer science or related field paired with knowledge, skills and abilities typically gained from 2-5 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