Distributed Cloud Computing Expert

3 days ago

kollam, India beBeeSeniorAi Full time

Senior AI Engineer RoleThis is a unique opportunity to solve intricate technical challenges, push the boundaries of what's possible with distributed graph computing and build a platform that fights financial crime.Impact: You will shape the architecture of an essential platform for enterprise decision-making.Innovation: The role offers the chance to work on advanced network graph technologies, big data pipelines, and cutting-edge AI/ML technologies.Growth: You will influence core engineering and play a central role in building the early team.Learning: Our company provides comprehensive onboarding on our ecosystem. It offers continuous learning opportunities and mentorship from senior Data Analytics & AI practitioners.Flexibility & Equity: This is your opportunity to be more than just an employee and become an entrepreneur in the true sense where you have significant upside as our organization grows into the future. Eventually, you will earn great base salary, significant early-stage equity, learning resources, and a high-impact remote-first culture.Main ResponsibilitiesEntity Resolution ServiceWe are looking for a skilled entity resolution service developer who can design and implement distributed entity resolution algorithms to process billions of records.The ideal candidate should be able to build blocking strategies (e.g., LSH, canopy clustering) optimized for Spark at scale.Create AI/ML based advanced matching with explainable AI (XAI).Implement incremental resolution supporting real-time and batch modes.Design APIs for entity lookup with sub-100ms latency requirements.Assist the team in building dynamic entity resolution with embedded graph knowledge of GNN and GT (Graph transformers).Network Generation ServiceArchitect distributed graph generation pipelines using libraries such as GraphX/GraphFrames.Implement graph analytics algorithms such as PageRank, community detection, and centrality measures.Design storage strategies for multi-billion edge graphs in the cloud.Build temporal graph support for time-evolving networks.Create high-performance graph serving APIs with complex query capabilities.Optimize graph partitioning to minimize shuffle and maximize locality.Ai/ml Model Development & Explainable Ai (xai)Develop Graph Neural Networks (GNNs) and models using neighbour sampling techniques such as GraphSAGE to analyze corporate and transaction networks for fraud and risk patterns.Implement AI based Entity Resolution algorithms using techniques such as fuzzy matching, semantic matching (Sentence-BERT), and clustering across heterogeneous data sources.Create Risk Scoring Models by combining rule-based, supervised and unsupervised methods, optimized for real-time and large data processing.Champion model transparency and fairness by integrating state-of-art models evaluation techniques such as SHAP, LIME, bias detection and monitoring model drifts.Minimum Qualifications:3+ years of experience in distributed computing and big data systems.2+ years' experience in entity resolution and graph analytics at scale.Strong understanding of blocking algorithms, probabilistic record linkage, and similarity measures.Ability to design and optimize large Apache Spark workloads.Ability to implement graph algorithms in distributed computing frameworks such as Apache Spark, Dask or equivalent with optimized queries and storage formats.Familiar with Elasticsearch or equivalent for fast search and pattern matching.Understanding of AI/ML applications to entity resolution.

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