# Umed Gill

> Senior Software Engineer | IIT | Rust | ML Infra

Location: San Francisco, California, United States
Profile: https://flows.cv/umed

With 4 years of experience as a Software Engineer and a foundation from IIT Varanasi, I specialize in building scalable, high-performance systems. My expertise spans Python, C++, Rust, Scala, and distributed computing frameworks, enabling me to deliver impactful solutions across diverse domains.  

 **Innovative Problem Solver:** Designed and implemented efficient Pricing and Pacing algorithms using Rust, driving system performance and scalability.  
 **Expert in Distributed Systems:** Built robust data pipelines and automation with Spark, Hadoop, Redis, Kafka, and AWS.  
 **Versatile Tech Stack:** Proficient in Docker, Kubernetes, ElasticSearch, SQL, Postgres, and ClickHouse for seamless data management.  
 **Collaborations:** Worked cross-functionally to deliver end-to-end solutions, combining technical depth with business impact.  

Always Passionate about complex challenges!

## Work Experience
### Senior Software Engineer @ Aarki
Jan 2024 – Present | San Francisco, California, United States
Pricing Algorithms. Real time bidding. DNN integration. Distributed Computing. C++. Rust. Python. Scala. Spark. Hadoop. SQL. Postgres. Athena. AWS. Kafka. Docker. Elastic Search. Clickhouse

### Data Engineer @ Aarki
Jan 2023 – Jan 2024 | San Francisco, California, United States
Fraud detection. Rust. Aerospike. Transient features development. Data pipelines. Automation. Redis. Shell scripts. Luigi. PySpark.

### Solutions Engineer @ LG Ad Solutions
Jan 2021 – Jan 2023 | Mountain View, California, United States
🔹 Logs Pipeline: Developed a Scala Spark job that processes over 3 TB of data per hour, transforming raw logs from S3 to HDFS with partitioning and converting data from CSV to Parquet for optimized storage and querying. Designed aggregated pipelines tailored to clubbed use cases for targeted analysis. Utilized Airflow for scheduling, setting up alerts, enforcing SLAs, and ensuring optimal resource utilization.
🔹 Deduplication Theory and Factor Generation: Developed a data-intensive algorithm using PySpark to identify and categorize duplicate requests, helping generate available inventory. Integrated ElasticSearch for efficient indexing and retrieval of duplicate data and used Athena for fast querying of large datasets. Automated the entire deduplication process through Airflow, ensuring efficient handling of large-scale data and improving data quality for better inventory management.
🔹 Alerting Mechanism: We developed a scalable alerting system in Node.js to manage 500+ supply and demand tags, triggering real-time alerts when spending exceeded thresholds or irrational numbers were detected. The solution leverages Node.js, Redis, and AWS, ensuring low-latency monitoring and automated alerts via Slack and email. This system streamlined anomaly detection, reducing manual oversight and enabling faster decision-making.

### Software Engineer Intern @ FPL Technologies
Jan 2020 – Jan 2020 | Pune, Maharashtra, India
• Developed a real-time dashboard using React admin and loopback client to enhance customer query resolution and calculate KPIs for strategic decision-making.
• Implemented Role-Based access controls with Casbin, third party logins, AWS authentication, and AUTH0 for enhanced security measures.
• Leveraged IBM Cloud's Watson Assistant and Discovery services to build a chatbot with 120+ intents for improved customer interactions.

### Vice President @ BloodConnect Foundation
Jan 2018 – Jan 2019 | Varanasi, Uttar Pradesh, India

### Summer Research Intern @ Indian Institute of Foreign Trade
Jan 2018 – Jan 2018 | Kolkata, West Bengal, India


## Education
### Indian Institute of Technology (Banaras Hindu University), Varanasi
Jan 2016 – Jan 2021


## Contact & Social
- LinkedIn: https://linkedin.com/in/umed-singh-0002

---
Source: https://flows.cv/umed
JSON Resume: https://flows.cv/umed/resume.json
Last updated: 2026-03-23