Sriram Sai Krishna

About Sai Krishna Sriram.

I'm a Master's graduate in Data Science from the University of Colorado, Boulder, with expertise in data analysis, data engineering, machine learning, and generative AI.

I specialize in building production-ready Generative AI solutions with LLMs, RAG, and prompt engineering. I have hands-on experience in transforming data into actionable insights, building scalable data pipelines, and developing AI-driven solutions. Whether it's deploying LLM applications, analyzing trends, or optimizing systems, I'm driven by turning data and AI into impactful outcomes.

Experiences

My professional and academic experience across Generative AI, LLM applications, data engineering, AI/ML, and IoT technologies.

Professional Experiences

AI/ML Engineer

CLD-9 | Boulder, Colorado

Productionized the LLM recommender as a FastAPI service on AWS with MLflow and CI/CD; added validation, rate limits, timeouts, and safe rollback. Built a serverless blood-report OCR pipeline using S3 events, EventBridge, Step Functions, PyMuPDF, and Mistral/Pixtral OCR Lambdas; sub-minute processing for multi-page PDFs. Working on a Blood Report Insights layer that normalizes ranges, flags out-of-range values, and maps findings to precautions or supplements; reliability via retries and failure thresholds.

AI/ML Intern

CLD-9 | Boulder, Colorado

Prototyped an LLM supplement recommendation engine (OpenAI API + RAG over vetted medical sources) with interactive follow-ups and grounded citations. Built retrieval/ranking with OpenAI embeddings, business-rule and contraindication filters, and prompt templates; improved relevance about 35% and reduced hallucinations about 20%. Established evaluation & feedback loops (precision@k, NDCG, factuality checks, user feedback) that cut manual review about 60%.

AI Engineer Intern

ASANTe | Boulder, Colorado

Shipped Flask and gRPC NLP services on AWS Lambda; integrated OpenAI text-embedding-3-large, improving recommendation accuracy by 18%. Built hybrid recommenders (collaborative, content-based, and sequential/BST) across retail, business, and nonprofit use cases. Ran Airflow pipelines for ingestion, embeddings, training, evaluation, and drift; automated reports and Tableau dashboards for KPIs.

ETL Developer

AbsoluteLabs. | Hyderabad, India

Built Databricks PySpark/Hive pipelines processing 5M+ records/day; optimized joins and aggregations to cut ETL runtime about 20% and meet SLAs. Curated feature-ready datasets in Snowflake and engineered Python (pandas/NumPy) features; wrote advanced SQL (CTEs, window functions) to surface demand forecasts, stock-out risk, and regional trends; delivered Power BI dashboards for store-level KPIs. Implemented Prometheus/Grafana monitoring and schema-change alerts; added data-quality checks (volume, freshness, validity) to catch anomalies early.

Data Engineer (Engineer I)

TCS - Qualcomm | Hyderabad, India

On-site at Qualcomm, built an ML analytics pipeline using Kafka and Scala to stream logs into Elasticsearch with archival on Amazon S3 Glacier; added autoencoder-based anomaly detection and confusion-matrix reporting; QlikView dashboards reduced failure triage time by about 30%. Developed Python packet-level TCP/UDP diagnostics integrating iPerf to quantify latency and throughput at OSI Layers 3 and 4, catching degradations during Wi-Fi and cellular handoffs. Created Java automation suites for Android 15/16 across Wi-Fi, Bluetooth (BlueZ), cellular (LTE/6G, IMS), camera, and sensors; containerized and shipped services with Docker/Kubernetes; and set up Jenkins CI/CD, coordinating global releases.

Cloud-IoT Data Eng. Intern

TCS | Hyderabad, India

Built an IoT telemetry ingestion pipeline using Raspberry Pi 3B+, DHT22 & MQ-135 sensors, Flask REST APIs, AWS EC2/S3 storage, and PostgreSQL analytics. Created Grafana real-time dashboards to monitor environmental trends.

Machine Learning Intern

Career Launcher | New Delhi, India

Built a pandas pipeline for equity OHLCV (CSV ingest, datetime casting, features: daily percent change, VWAP, rolling volatility, SMA/Bollinger) with EDA visuals and correlation analysis. Estimated OLS beta and CAPM-style risk; trained a Random Forest trade-call classifier with out-of-sample evaluation and cumulative-return backtests; optimized portfolios via the efficient frontier and validated diversification with K-means.

IoT Data Eng. Intern

ECIL | Hyderabad, India

Developed an Arduino Uno–based weather monitoring system with DHT11 & BMP180 sensors, streaming to Firebase Realtime DB for cloud-based storage. Automated data cleansing and aggregation in Python (pandas, matplotlib).

Academic Experiences

Oct 2023 - May 2025

Grad. Research Assistant

CU Boulder | Boulder, Colorado

Conducted advanced research in robotic manipulation and computer vision within the HIRO Group. Integrated AI-driven spatial estimation algorithms with robotic arms for dynamic task execution and human-robot interaction scenarios. Developed novel approaches for real-time object recognition and spatial mapping, contributing to cutting-edge robotics research and autonomous system development.

Apr 2024 - May 2025

Grad. Teaching Assistant

Coursera CU Boulder | Boulder, Colorado

Facilitated multiple data science courses and developed comprehensive automated grading systems for online learning platforms. Taught core concepts in Data Mining, Machine Learning, and Data Structures while creating Python-based assessment tools with Docker containerization. Provided personalized feedback and support to students, improving learning outcomes and course engagement metrics.

Aug 2023 - May 2025

M.S. in Data Science

CU Boulder | Boulder, Colorado

Comprehensive program covering advanced data science concepts including data mining, big data architecture, and machine learning fundamentals. Specialized in neural networks, deep learning, natural language processing, computer vision, and robotics applications. Developed expertise in building scalable ML solutions and deploying models to cloud platforms with focus on real-world applications and industry best practices.

B.Tech. in ECE

GRIET | Hyderabad, India

Strong foundation in electronics and communication engineering with specialized computing electives and hands-on project experience. Core coursework included data structures, algorithms, probability, statistics, linear algebra, signals and systems, database management, and computer networks. This comprehensive combination provided excellent preparation for data science and machine learning applications in modern technology environments.

Skills

A versatile skill set spanning Generative AI, LLM applications, machine learning, data engineering, cloud computing, and programming, enabling impactful and scalable AI solutions.

Generative AI

Building production-ready LLM applications with RAG, fine-tuning, and prompt engineering. Experienced with OpenAI API, LangChain, and AWS services for deploying scalable generative AI solutions.

Machine Learning

Designing and implementing machine learning models for predictive and classification tasks. Experience with frameworks like TensorFlow, PyTorch, and scikit-learn for end-to-end ML pipelines.

Data Engineering

Building scalable ETL processes and real-time data pipelines to support large-scale data operations. Proficient in tools like Apache Spark, Databricks, and cloud-based platforms like AWS and Azure.

Data Analysis

Extracting insights from complex datasets using statistical methods and visualizations. Skilled in Python, R, and SQL for exploratory data analysis, trend detection, and predictive modeling.

Cloud Computing

Skilled in leveraging AWS, Azure, GCP services for scalable and efficient cloud solutions. Proficient in Python, Bash scripting, with experience in Java, Scala, and C++ for versatile software engineering tasks.

Data Visualization

Transforming data into meaningful visual stories using Tableau, Power BI, and Matplotlib. Creating dashboards that enhance decision-making and improve business efficiency.