كبير مهندسي الرؤية الحاسوبية

Job description

You will lead Valify’s Machine Learning department end to end, overseeing the models powering our identity-verification products and the engineers who build them. The role covers Computer Vision and NLP, with a strong focus on production deployment, evaluation, version control, and rollback procedures.

This is a hands-on leadership role in a regulated environment, with models deployed on-premises, through APIs, and mobile SDKs. You will report to the Technology Lead, manage and mentor the ML team, and represent the function in technical and regulatory discussions.

A key responsibility is building and growing the team through hiring, development, and performance management, while ensuring the department meets its KPIs and continuously improves its engineering and operating standards.

Responsibilities

• Own model quality across our entire stack: benchmarks, regression gates, and release sign-off before

anything reaches a client environment.

• Lead and grow the ML team — supervision, technical review, development plans, and hiring.

• Set the technical direction for the department’s highest-risk services and oversee the response to

emerging fraud techniques.

• Lead the research and proof-of-concept development behind new products and capabilities.

• Direct the annotation team: scope labeling requirements, set annotation guidelines, and sign off on

data quality before it enters training.

• Maintain the evidence trail that regulated clients and auditors require.

• Build evaluation and telemetry infrastructure across all deployments.

Requirements

• 5+ years of professional experience in machine learning or applied AI, including at least 2 years

leading engineers or owning a production ML pipeline.

• Bachelor’s degree in computer science, computer engineering, or a related quantitative field; a

postgraduate degree is a plus.

• Deep expertise in computer vision — detection, OCR, classification, segmentation, and image quality

assessment, or comparable computer vision domains — with working competence in NLP.

• Proven ownership of ML systems in production, covering deployment, monitoring, maintenance, and

rollback.

• Demonstrated experience optimizing model performance — latency and resource footprint —

including quantization, pruning, or distillation for inference on constrained client hardware.

• Proven experience leading a model evaluation process.

• Experience overseeing the data annotation process end to end, from scoping through quality control.

• Experience managing engineers directly, including technical review and development planning.

• Proven experience in deployment in constrained environments: on-premises or air-gapped

environments, client-controlled infrastructure, or regulated industries.

Valued but not required

• Prior work on identity verification, biometrics, KYC, or document understanding.

• Experience with Arabic OCR, including optimizing, training, or fine-tuning such models.

• Exposure to regulator-facing work: audits, model documentation, compliance evidence.