Head Platform Engineer

5 days ago

Bengaluru, India Neemtree Full time

Responsibilities : - Build and scale ML engineering and data engineering functions.- Establish MLOps frameworks for standardised, production-grade model development and monitoring.- Ensure smooth model transition from data science experimentation to live deployment.- Design and operationalise a centralised decisioning platform that integrates low-code model development, AutoML, rule engines, and workflow automation.- Enable DS and Risk teams to build, test, and deploy models with minimal engineering bottlenecks.- Expand decisioning systems across functional podscredit, pricing, collections, fraud, cross-sell, and customer management drive consistent, explainable, and auditable decision-making.- Ensure the platform is scalable, modular, and compliant with RBI regulations.- Build modern, scalable data platforms (real-time ingestion, lakehouse, event-driven systems).- Ensure full lifecycle governance of data from sourcing to archival.- Partner with governance teams to enable lineage, auditability, and regulatory compliance.- Lead DataOps, L1/L2 support, and SRE teams to maintain > 99.5% platform uptime.- Implement automated testing, proactive monitoring, and self-healing systems.- Optimise infra utilisation and cloud cost efficiency.- Act as execution partner to the Head of Product and Strategy and functional leaders.- Deliver platform capabilities and decisioning products aligned to business KPIs (loan volume growth, risk reduction, ticket size expansion, collections efficiency).- Manage technology partnerships and vendor ecosystems (e. g., Databricks, automation tools).Requirements : - 15 ~ 20 years of experience in data engineering, ML engineering, or platform leadership, with at least 8 ~10 years in senior management roles.- Proven success in building and scaling large-scale data/ML platforms in fast-paced environments (fintech preferred).- Strong academic foundation with Bachelor's/Master's/PhD in Computer Science, Engineering, or quantitative fields from top-tier Indian institutions (IIT/IISc/BITS/NIT).- Deep expertise in data platform design (streaming, lakehouse, event-driven, real-time ingestion).- Hands-on knowledge of MLOps frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI).- Strong background in model lifecycle managementdeployment, monitoring, retraining, and governance.- Experience operationalising decisioning platforms combining rules, ML, AutoML, and workflow automation.- Expertise in distributed computing and big data frameworks (Spark, Hadoop, Kafka, Flink).- Proficiency in cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).- Strong understanding of data governance, lineage, and compliance frameworks in regulated industries (RBI, GDPR).- Solid programming and scripting experience (Python, SQL, Scala/Java) with knowledge of ML/DL libraries (TensorFlow, PyTorch, Scikit-learn).- Track record of driving platform reliability, resilience, and performance through DataOps and SRE practices.- Ability to manage and optimise infra utilisation and cloud costs at scale.- Excellent leadership skills with experience managing 15+ member teams across engineering and platform functions.- Strong communication, stakeholder management, and vendor negotiation skills to bridge business and technology. (ref:hirist.tech)

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