Senior Machine Learning Developer
Core
Operationalize advanced machine learning, User Behavior Analytics (UBA), and GenAI solutions to model and predict behaviors for proactive threat detection and response in a global digital landscape.
Role type
Senior Machine Learning Developer (Security & Fraud)
Builds
Production-grade AI solutions for Cyber, Fraud, Risk, and Security teams using on-prem/cloud-native tools.
Domain
Financial Services / Cybersecurity / Machine Learning
Deliverable
production ML models
Required skills
Python, PySpark, SQL, Neo4j (Cypher), PyTorch, REST API development, CI/CD automation, MLOps, graph database management, data pipeline engineering, model deployment and monitoring.
Preferred skills
LLM deployment, RAG systems, agent orchestration frameworks (LangChain, CrewAI), AWS cloud services, observability stacks (Grafana, Prometheus), secure coding practices.
Technologies
AWS SageMaker, Kubernetes, Docker, Neo4j, Cloudera Data Lake, OpenShift, GitHub Actions, Jenkins, Prometheus, Grafana, Langfuse, FastAPI, Django, Snowflake, Postgres, MongoDB, PySpark, Airflow, JupyterHub, RunAI, Helios.
Responsibilities
Engineer and maintain scalable data pipelines and workflows; build pipelines to integrate ML/UBA detections into a graph knowledgebase; optimize Spark job performance; deploy and manage ML and Agentic applications; apply best practices in secure coding and MLOps CI/CD automation; contribute to code reviews and technical documentation; champion AI safety and regulatory compliance.
Seniority
Senior, hands-on IC
