Senior Machine Learning Engineer

Role Overview:

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative Data Science and Engineering team. Reporting to the Data Science Director, you will play a critical role in building and scaling machine learning systems that power our cybersecurity products. You will work closely with data scientists and software engineers to design, develop, and deploy end-to-end ML pipelines, ensuring high performance and reliability in production. Your engineering expertise will directly contribute to solving complex challenges in areas such as threat detection, malware analysis, anomaly detection, and automated model workflows.

About the role:

• As a Senior Machine Learning Engineer, you will be part of a high-impact team reporting to the Director of Data Science, focused on developing scalable, production-grade machine learning solutions to power cybersecurity products.
• Collaborate with data scientists and engineering teams to build and scale machine learning pipelines.
• Develop and deploy production-ready ML systems for use cases such as:Threat and attack detection,Threat hunting,Malware detection,Anomaly detection
• Build and optimize distributed data pipelines using Apache Spark and Python.
• Design and implement MLOps workflows including data preprocessing, model training, evaluation, and deployment.
• Monitor and retrain ML models based on feedback and performance in production.
• Develop model serving infrastructure for high availability, low latency, and scalability.
• Automate and streamline feature engineering, hyperparameter tuning, and CI/CD pipelines for ML models.
• Ensure model integration into security products with adherence to compliance and data governance standards.

About you:

You are an experienced ML Engineer with a strong foundation in software engineering and a passion for solving complex problems in the cybersecurity domain.

Must-Have Qualifications:

• A Master Degree or Equivalent degree in Machine Learning, Computer Science, or Electrical Engineering, with Mathematics/Statistics at undergraduate level
• 4-6 years of industry experience as a Machine Learning Engineer
• Advanced proficiency in Python and strong programming fundamentals
• Hands-on experience with Apache Spark or PySpark for distributed data processing
• Solid understanding of machine learning concepts and experience with ML libraries like scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Experience in building, deploying, and monitoring end-to-end ML systems in production
• Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker Pipelines).
• Proficiency in SQL and handling large-scale data
• Experience working with public cloud platforms (AWS, GCP, or Azure).
• Strong software engineering practices: Git, containerisation (Docker), testing, CI/CD

Good to Have:

• Knowledge of Large Language Models (LLMs) such as GPT, BERT, LLaMA, or Falcon.
• Experience with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG)