Senior AI/Machine Learning Engineer

1 week ago

Solapur, Maharashtra, India beBeeArtificialintelligence Full time US$ 18,00,000 - US$ 25,00,000

Job Title: Senior AI/ML Engineer

About the Role

As a senior expert, you will lead the development of our Entity Resolution and Network Generation services.

This role involves architecting and implementing distributed graph computing solutions that process large amounts of data.

The Platform

We leverage microservices architecture with Kubernetes orchestration, Apache Spark for distributed processing, Elasticsearch for real-time search and fuzzy matching, Scala as the primary development language.

Data Mesh principles guide our approach with API-first design.

Key Responsibilities
  1. Entity Resolution Service: Design and implement algorithms capable of processing large datasets.
  2. Build blocking strategies: Optimize LSH and canopy clustering for Spark at scale.
  3. Fuzzy matching algorithms: Leverage Elasticsearch's capabilities to develop effective match strategies.
  4. ML-enhanced matching: Implement explainable AI for match decisions.
  5. Incremental resolution: Support real-time and batch modes.
  6. APIs for entity lookup: Design APIs with sub-100ms latency requirements.
Network Generation Service
  1. Distributed graph generation pipelines: Architect using GraphX/GraphFrames.
  2. Graph analytics algorithms: Implement PageRank, community detection, centrality measures.
  3. Storage strategies: Design storage for multi-billion edge graphs in Parquet/distributed file systems.
  4. Temporal graph support: Build temporal graph support for time-evolving networks.
  5. Graph serving APIs: Create high-performance graph serving APIs with complex query capabilities.
  6. Optimize graph partitioning: Minimize shuffle and maximize locality.
Ai Model Development
  1. Build Graph Neural Networks (GNNs): Develop GNN models (e.g., GraphSAGE, GATv2) using PyTorch Geometric or DGL.
  2. Implement Entity Resolution: Design algorithms for fuzzy matching, semantic matching (Sentence-BERT), and clustering.
  3. Create Risk Scoring Models: Combine rule-based, supervised (XGBoost), and unsupervised (Isolation Forest) methods to generate composite risk scores.
  4. Advance Composite Ai: Leverage proprietary approach integrating symbolic AI, vector embeddings, and graph AI for robust entity resolution and network analytics.
Cross-Service Responsibilities
  1. Ensure seamless integration: Between entity resolution and network generation services.
  2. Design data lineage tracking: Across both services.
  3. Implement comprehensive monitoring: And observability.
  4. Contribute to API design: And service contracts.
  5. Optimize for scale growth: Prepare for 10x scale growth.
Benefits

This role offers the opportunity to work on cutting-edge AI/ML projects and collaborate with experienced professionals in the field.

As a member of this team, you will have access to state-of-the-art technologies and tools to help you grow your skills and expertise.

Requirements
  • Strong background in AI/ML engineering.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Experience with distributed systems and big data processing.
  • Familiarity with cloud platforms such as AWS or GCP.
Preferred Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • Prior experience working with graph databases and neural networks.
  • Familiarity with DevOps practices and containerization.

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