The client is looking for experienced ML Engineer specializing in anomaly and fraud

detection for their cyber security team. The ideal candidates will have strong expertise

in ML, deep learning, and time series analytics, with a proven ability to work with large-

scale datasets. Strong storytelling skills to communicate insights to non-technical

stakeholders are crucial.

Key Responsibilities:

Lead and contribute to the full lifecycle of AI/ML projects, from problem definition and data exploration to model development, deployment, and monitoring in the Azure cloud environment with Azure Databricks.
Apply a strong foundation in deep learning, probabilistic modeling, and time series clustering techniques and their productionization to solve problems such as anomaly detection and fraud detection
Develop and scale production ready ML models for anomaly and fraud detection.
Work with Python, TensorFlow, XGBoost and other explainable models, Azure DBP (must) and Azure Databricks (preferred).
Conduct threat hunting and cybersecurity-related analytics (bonus).
Handle large-scale data processing and drive insights.
Translate complex ML models into explainable and actionable business insights for non-technical audiences.
Conduct thorough data analysis, feature engineering using feature store, and model evaluation to ensure high-performing and reliable solutions.
Troubleshoot, debug, and optimize AI/ML models and pipelines for performance and scalability, ensuring continuous improvement and alignment with evolving business needs.
Take ownership and lead parts of the project to deliver high-impact AI solutions that align with business objectives.
Engage with all stakeholders to present technical concepts and solutions in business-friendly terms, ensuring alignment with strategic goals.

Qualifications

Strong past experience in ML engineering and data science, with at least 5-10 years of experience in machine learning and anomaly detection.
Strong Python proficiency with hands-on experience in TensorFlow, XGBoost, time series analytics and Azure DBP.
Hands-on experience with large-scale datasets and probabilistic modeling.
Ability to communicate complex ML concepts effectively.

Domain Expertise (Preferred)

Prompt Engineer- work from home- 1 to 2 years- Upto 10 Lakhs PA

Principal ML Engineer