Chief Graph Computing Specialist

11 hours ago

India beBeeMachineLearning Full time ₹ 1,00,00,000 - ₹ 1,50,00,000
Job Opportunity: Senior AI/ML Engineer

This is a hands-on technical leadership role where you'll architect and implement distributed graph computing solutions processing massive datasets and relationships.

Key Responsibilities:
  • Design and implement scalable entity resolution algorithms capable of processing billions of records.
  • Develop fuzzy matching algorithms leveraging Elasticsearch's advanced capabilities.
  • Create ML-enhanced matching with explainable AI for decision-making processes.
  • Implement incremental resolution supporting real-time and batch modes.

Additionally, you will be responsible for:

  • Architecting large-scale distributed graph generation pipelines using Graph X/Graph Frames.
  • Implementing graph analytics algorithms (Page Rank, community detection, centrality measures).
  • Designing storage strategies for multi-billion edge graphs in Parquet/distributed file systems.

And lead the development of our Entity Resolution and Network Generation services.

The platform leverages microservices architecture with Kubernetes orchestration, Apache Spark for distributed processing, Elasticsearch for real-time search and fuzzy matching, Scala as the primary development language, and data mesh principles with API-first design.

Requirements:
  • 7+ years of experience in distributed computing and big data systems.
  • 5+ years specifically in entity resolution and graph analytics at scale.
  • Expert-level Scala programming skills.
  • Deep experience with Apache Spark, including custom optimizations.

And strong understanding of blocking algorithms and their trade-offs, experience with probabilistic record linkage and similarity measures, expertise in graph algorithms and their distributed implementations, knowledge of graph storage formats and query optimization, and understanding of ML applications in entity resolution.

Preferred Qualifications:
  • PhD in Computer Science or related field with focus on graphs/entity resolution.
  • Contributions to open-source projects (especially Spark, Graph X, Elasticsearch).
  • Experience with graph databases (Neo4j, Neptune, Janus Graph) or equivalent.
  • Publications or conference talks on entity resolution or graph analytics.

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