Senior Machine Learning Engineer

Job description

You will lead Valify's machine learning department end to end: the models behind our identity-verification

products, the engineers who build them, and the standards they are built to. The ML surface spans

computer vision and NLP in production today and will expand as Valify's products and markets grow.

This is a hands-on leadership role in a regulated environment. Models are deployed on premises into client

infrastructure or via API and mobile SDK; the role therefore demands experience in deployment, in

evaluation gates, version discipline, and rollback procedures. You will report to the Technology Lead,

manage the ML engineers directly, and represent the ML team in technical and regulatory discussions.

Building the team is a core part of the role: you will be responsible for hiring new ML engineers, alongside

the supervision and development of the engineers working within it. The department's operating

standards, evaluation methodology, and hiring frameworks are documented. Your role is to make sure the

team runs in line with those guidelines and meets the department's KPIs, and to improve both as the team

grows.

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.