Yashwanth Reddy Boddireddy
Where Data Meets Development
Transforming complex data into intuitive solutions through full-stack development and data science
4+
Years Experience
15+
Projects Completed
10+
Technologies Mastered
My Journey
From Electrical Engineer to full-stack data development, my path has been driven by a passion for solving complex problems with data and code.
Yashwanth Reddy Boddireddy
At the intersection of AI innovation and data science, I transform complex problems into impactful solutions that drive measurable business outcomes.
Software Engineer specializing in AI applications and machine learning, helping organizations leverage data for competitive advantage. With experience at Accenture and Headstarter AI, I focus on developing intelligent systems that enhance user experiences.
I combine technical expertise with business acumen, following a systematic approach: understanding requirements, designing data-driven architectures, and implementing scalable solutions with measurable results.
Master of Science in Data Science, Statistics @ New Jersey Institute of Technology (NJIT), Newark, NJ
AI Engineer @ JPMorgan Chase & Co. — Remote, USA
- Own the inference platform that serves 60K+ predictions daily across enterprise analytics workloads. Set it up on Kubernetes with EC2 GPU instances, currently sitting at 99.8% uptime.
- Built out the RAG and anomaly detection pipelines using LangChain, OpenAI API, and PyTorch. The anomaly detection piece alone improved accuracy by about 31% over what was there before.
- Worked closely with DevOps to get our FastAPI microservices into a proper CI/CD flow with MLflow and Airflow. Cut deployment time roughly in half.
- Spent a good amount of time on GPU optimization with TensorRT, got utilization up 28%. Also set up the Prometheus/Grafana dashboards the team now uses daily.
- Helped compress our prototype-to-production timeline from ~2 weeks down to 5 days by working directly with the data science team and mentoring a few junior engineers through the process.
AI Engineer @ VMware (Broadcom) — Remote, USA
- Owned the predictive analytics pipeline end-to-end — training, validation, deployment. PyTorch models with MLflow tracking and Airflow orchestration. Helped cut incident response time by around 40%.
- Put together NLP services for semantic search across internal knowledge bases using Hugging Face Transformers and LangChain, wrapped in FastAPI.
- Brought inference latency down 27% by moving to TensorRT and Ray Serve. Most of this was profiling work to find where the bottlenecks actually were.
- Partnered with the cloud team on AWS infrastructure (S3, EC2, Lambda) and Kubernetes deployments. A lot of this was making sure our data pipelines were reproducible and properly versioned.
Data Scientist @ Accenture — Hyderabad, India
- Built NLP chatbots and recommendation engines on Azure OpenAI and Hugging Face that increased user engagement by 22% for clients.
- Set up the team's MLOps platform from scratch — Databricks, Airflow, MLflow, Docker. Before this, model handoffs were mostly manual. Took about 45% off delivery timelines.
- Built multi-agent systems with LangChain, LlamaIndex, and Pinecone/FAISS for document Q&A. One Fortune 100 client reported it cut analyst research time by 60%.
- Helped modernize a 5 TB/day streaming pipeline on AWS Glue and Kinesis — integrated with legacy systems without downtime and got throughput up about 30%.
- Managed a team of 5 (mix of engineers and data scientists). Introduced code review standards and AI governance processes. Shipped 7 models to production that year.
Technical Proficiency
A comprehensive overview of my technical skills in AI engineering, MLOps, generative AI, cloud infrastructure, and data engineering.
Core Competencies
Featured Work
A showcase of my projects spanning production RAG systems, LLM observability, AI applications, and data analytics.
Get In Touch
Have a project in mind or interested in working together? I'd love to hear from you. Let's create something amazing.