Overview

We are seeking a technically deep Machine Learning Engineer to join our Security & Identity team. This role is ideal for someone who enjoys working at the intersection of graph data modelling and applied machine learning.

Key Responsibilities

• Design and implement graphbased models to represent complex identity and access relationships.
• Develop and deploy MLdriven anomaly detection capabilities.
• Build and optimize cloudnative data pipelines to support largescale analytics in enterprise environments.

Required Skills

• Python, pandas, scikitlearn with 3+ years of handson experience
• Strong experience with AWS (S3, Glue, Lambda, Step Functions) – 2–3+ years
• Handson experience with Neo4j and Cypher, including exposure to Neo4j GDS (minimum 1 year or 1+ major project)
• Working experience of Graph Neural Networks (GNNs)
• 2+ years of experience in unsupervised ML and anomaly detection
• Proven experience building and deploying ML services / APIs
• Experience integrating ML solutions with LLM platforms (Bedrock, SageMaker, OpenAI) – at least one project

Preferred Skills

• Exposure to IAM, identity, or security analytics
• Knowledge of SAP Security / SoD concepts
• Familiarity with Active Directory / Azure AD
• Exposure to SAP SuccessFactors

Qualifications

• Location: Remote/Hybrid
• Shift: EST
• Experience: 5–8+ years overall, 3+ years in ML, 1–2+ years with graph analytics / graph DB