Mr. Abhishek Das

Abhishek Das is a highly accomplished software engineer with over a decade of experience in building scalable and innovative technology solutions across multiple industries. Currently, he serves as a Software Engineering Lead at Salesforce, where he plays a crucial role in developing the Einstein Machine Learning platform for real-time inference, enabling enterprise-level AI solutions. His expertise in cloud computing, distributed systems, and artificial intelligence has significantly contributed to the success of Salesforce’s AI initiatives. Prior to this role, Abhishek worked at Microsoft for nearly five years, where he held key leadership positions and contributed to major projects such as Azure Dedicated and Azure Stream Analytics. At Azure Dedicated, Abhishek led the network control plane for building Baremetal as a Service for dedicated workloads, successfully onboarding Nutanix as the first workload. He made several improvements in the stack and mentored new engineers, helping to create a more efficient and high-performing team. His earlier work at Azure Stream Analytics involved leading the control plane effort for stream analytics on edge devices and delivering new features such as auto-scaling, parquet input, and customer-provided storage. Abhishek also played a critical role in enabling data plane migration from HDInsight to Service Fabric, ensuring a seamless and resilient orchestration process. His technical leadership and problem-solving skills were instrumental in the success of these projects. Before joining Microsoft, Abhishek worked at Groupon as part of the computational marketing team, focusing on display ads engineering. He contributed to optimizing marketing solutions using data-driven approaches to improve customer engagement and business outcomes. His time at Dell EMC further refined his expertise in data protection and availability solutions. During his tenure, he received the prestigious EMC Excellence Award for providing critical patches that unblocked issues in a large CSV environment. He also holds a patent for optimizing the backup of clusters with multiple proxy servers, demonstrating his ability to innovate and solve complex technical challenges. Abhishek’s academic journey began at Odisha University of Technology and Research, where he earned his Bachelor of Technology degree in Computer Science. He later pursued a master’s degree in Computer Science from Texas A&M University, where he was involved in several innovative projects. One of his notable projects was a distributed password cracker, which simulated a distributed environment with multiple worker nodes and a metadata server. This project allowed him to explore various aspects of distributed systems such as load balancing and fault tolerance. Another significant project was Trivia Pitcher, an online multi-user trivia system that created trivia questions from a Neo4j graph database built from Wikipedia’s XML dump. The system provided questions based on user difficulty levels, showcasing his interest in building intelligent and interactive systems. Abhishek’s passion for technology extends beyond his professional work. He is dedicated to mentoring junior engineers and fostering a collaborative work culture. Known for his ability to think outside the box and deliver end-to-end solutions, Abhishek is widely respected in the tech community. His skills in distributed systems, cloud architecture, and AI have been endorsed by many colleagues and industry peers. With a relentless drive for innovation and a deep understanding of emerging technologies, Abhishek continues to push the boundaries of what is possible in software engineering.

• cloud computing
• SPARK SQL
• HIVE
• Postgres SQL
• Teradata
• SQL
• JavaScript
• node.js
• Artificial Intelligence
• Distributed Systems
• Java
• Hadoop
• Load Balancing
• Auto Scaling
• Emerging technologies
• Redis
• Edge Computing
• Junit
• Data Protection
• Data Migration
• cloud architecture
• Real-Time Inference
• Network Control
• Baremetal Services
• Service Fabric
• Control Plane
• Computational Marketing
• Display Ads
• Fault Tolerance
• Neo4j Database
• Innovation & Mentorship
• test NG
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