ML Engineer: End-to-End Model Deployment & Monitoring

INKOR; Fatih; On-site; TRY 350,000 - 700,000; Full time

Job summary

INKOR’s AI Lab builds the models behind INKOR products—from document understanding to forecasting. You will own the full lifecycle: data, training, evaluation, deployment and monitoring, taking models from notebooks to reliable production services used across the group.

Join a hands-on ML engineering role focused on building robust pipelines, evaluating models, and collaborating with product teams on model behaviour and guardrails.

Qualifications

• 3+ years of hands-on ML engineering experience.
• Must demonstrate strong Python, PyTorch or TensorFlow.
• Experience with MLOps tooling and containerised deployments.
• Solid understanding of evaluation methodology.

Responsibilities

• Prepare data pipelines and training workflows.
• Evaluate models with clear, reproducible benchmarks.
• Deploy and monitor models in production.
• Work closely with product teams on model behaviour and guardrails.

Skills

ML engineering

Python

Model evaluation

Research-to-prod

Tools

Python

PyTorch

TensorFlow

MLOps tooling

Containerised deployments

Job description

INKOR’s AI Lab builds the models behind INKOR products—from document understanding to forecasting. You will own the full lifecycle: data, training, evaluation, deployment and monitoring, taking models from notebooks to reliable production services used across the group.

Join a hands-on ML engineering role focused on building robust pipelines, evaluating models, and collaborating with product teams on model behaviour and guardrails.