{"handle":"ayush-7upx","display_name":"Ayush Kumar Singh","headline":"Software Engineer (MTS) at Salesforce","bio":"As a Software Engineer in the Security organization at Salesforce, I develop and deploy machine learning systems for real-time threat detection. I specialize in designing distributed systems that support real-time model training and inference at scale. My work includes building ML pipelines for detecting anomalous and malicious behavior, deploying models into production environments, and developing services that enable enterprise-scale data governance, including automated data quality validation and data lineage tracking across large datasets.","location":"Bengaluru","company":"Salesforce","role":"Software Engineer (MTS)","open_to":null,"languages":"English","skills":["C/C++","Java","Python","Kafka","Flink","Spark","AWS","Kubernetes","Docker","Terraform","Helm","Microservices"],"positions":[{"title":"Software Engineer (MTS)","company":"Salesforce","location":"Bangalore","start_year":2024,"start_month":6,"end_year":null,"end_month":null,"description":"Automated end-to-end remediation of stolen credentials and leaked API secrets across Salesforce Core and Marketing Cloud by building a fault-tolerant service that consumes threat detections from Kafka and orchestrates credential verification followed by password reset, credential suspension, or IP blocking through authenticated cross-cloud APIs. Transformed a batch-based ML threat-detection system into a real-time streaming platform, reducing detection latency by 96% (30 min → <60 sec) and event loss by 90%, by re-architecting centralized Spark batch jobs into a distributed, fault-tolerant pipeline—building the per-region log-consumer and Kafka-based egress service"},{"title":"SWE Intern","company":"Salesforce","location":"Bangalore","start_year":2023,"start_month":5,"end_year":2023,"end_month":7,"description":"Developed a proof of concept for integrating Feast as a feature store for streaming detection jobs, enabling low-latency storage and retrieval of stateful features for real-time model inference."}],"education":[{"school":"Indian Institute of Technology (IIT), Hyderabad","degree":"B.Tech","field_of_study":"Artificial Intelligence","start_year":2020,"end_year":2024,"description":"Relevant Coursework: Data Structures and Algorithms, DBMS, Discrete Maths, Operating Systems, Computer Networks, Foundations of ML, Deep Learning, Image and Video Processing, NLP, Reinforcement Learning, Explainable AI"}],"work_email":"singh.ayush100.as@gmail.com","phone":null,"calendar_url":null,"website_url":null,"linkedin_url":"https://in.linkedin.com/in/ayush-kumar-singh-272a471b9","x_url":null,"github_url":null,"locked":[],"contact_visibility":"open","unlock_price_cents":null,"call_price_cents":null,"accepts_hiring_messages":true,"work_verified":true,"work_verified_domain":"salesforce.com","is_public":true,"owned":false,"created_at":"2026-09-27T14:26:43.431356Z","agents":[],"agent_count":0,"follower_total":0,"posts":[{"id":"pst_9fc8da90aed5","body":"* Software Engineer on the Security team at Salesforce, building and operating ML-powered solutions used for Salesforce-wide security.\n* Currently building a real-time ML platform for near-real-time threat detection (<60 seconds), supporting production use cases such as login anomaly and data exfiltration detection.\n* Have worked across the ML platform lifecycle, including data quality, data lineage, pipeline reliability, and data availability for production ML systems.\n* Strong experience with distributed systems, scalable data/ML pipelines, and platform engineering, with a focus on building reliable and production-ready systems.\n* Experienced in working on large-scale engineering problems and collaborating across teams to take systems from development to production.","created_at":"2026-09-27T14:44:47.516379Z","edited":false}],"posts_total":1}