Machine Learning & Full-Stack Engineer

Manas Satish Singh

New York, NY *************@*****.*** +1-201-***-**** LinkedIn Github Portfolio Skills and Certifications

Languages: Python, Bash, JavaScript, Go, SQL, TypeScript, Java Frameworks/Libraries: Next.js, Scikit Learn, Nmap, Flutter, React.js, TensorFlow, PyTorch, PySpark MLOps and DevOps: AWS, GCP, Azure, Databricks, Kubernetes, Jenkins, ArgoCD, Kubeflow, Terraform, Langfuse, MLflow Data Visualization: Excel, Tableau, Power BI, looker Studio (Google studio), AWS QuickSight, Matplotlib, Seaborn, Matlab Databases: MySQL, Oracle DB, AWS DynamoDB, Redis, MongoDB, Snowflake, PostgreSQL Certifications: AWS Certified Solutions Architect – Associate

AWS Certified Machine Learning - Specialty

Databricks Certified Associate Developer for Apache Spark Publications

• “ML-Aided Autonomous Cloud Platform Service Management Framework,” IEEE 2025, New York, USA Link

• “ML-DaaS: An Integrated ML Training and Deployment Framework for Hybrid Cloud,” IEEE 2025, New York, USA Link Experience

Madison Square Garden New York, NY

Full Stack Software Engineer May 2026 – Present

• Extended ServiceNow's MCP interface to connect with external enterprise systems, allowing agents to read, update, and trigger workflows across platforms in real time

• Built an automated provisioning pipeline for AWS AgentCore memory and runtime, reducing multi-agent job setup from 2 hours and 15 manual steps to a single triggered process

• Automated customer-facing support flows in AWS Connect using AI-driven call routing, improving first-call resolution by ~45%

BAGR New York, NY

Full Stack Software Engineer October 2025 – April 2026

• Developed and optimized enterprise-scale data lakes using AWS Lake Formation and Apache Spark ETL pipelines processing 3+ TB/day, managing 20+ distributed clusters to refine ETL efficiency by 35% and reduce job failures by 25%

• Enhanced ML pipelines by setting up Kubeflow workflows with automated monitoring and logging via Grafana and Prometheus, accelerating deployments by 63% and achieving 95% model stability

• Modeled OAuth2.0-secured integrations and event-driven automation pipelines using n8n to orchestrate data flows between distributed services and production systems

• Trimmed Snowflake warehouse spend by 23% through targeted query tuning, table decommissioning, and tighter storage policies Sellwizr New York, NY

AI/ML Engineer (MlOps focus) May 2025 – September 2025

• Engineered agentic AI workflows on AWS Bedrock with policy guardrails, automated auditing, and tracing, reducing violations 30%

• Drove SOC2 compliance across 50+ security, privacy, confidentiality controls with single-tenant architecture, ensuring data governance, access management, and continuous monitoring for 15+ microservices

• Added a GitHub Actions CI pipeline (lint, typecheck, unit tests, Playwright E2E), reducing production regressions by 35% and shortening release cycles from 2 days to 8 hours

• Deployed Airbyte on AWS EKS using Helm and integrated dbt Core to build scalable, versioned ETL pipelines that populate a centralized data lake for ML training and inference workloads

• Managed CI/CD with Jenkins and Terraform syncing financial data across 5+ CRM platforms, achieving 85% faster deployments Stevens Institute of Technology Hoboken, NJ

Research Assistant January 2025 – May 2025

• Architected a self-healing private cloud with OpenStack, increasing uptime by 40% and halving VM provisioning time

• Created an edge computed framework with RaspberryPi on UAVs, boosting processing speed by 62% and reducing latency by 20%

• Implemented UAV IoT automation with Ansible and Terraform, reducing infrastructure setup time from 3 hours to 32 minutes

• Mentored students to deploy ML microservices and gRPC on cloud with secure IAM and service-to-service policies

• Achieved 84.89% accuracy in anomaly detection with hybrid LSTM-Autoencoder, outperforming 14 other ML/DL models Elenjical Solutions Hyderabad, India

DevOps Engineer January 2023 - July 2024

• Orchestrated K8s deployments for 15+ fintech engines using Argo CD (GitOps), automating scaling and cutting downtime by 15.5%

• Instrumented services with OpenTelemetry + dashboards/alerts, reducing MTTR from 2 hours to 20 min

• Hardened VPC/network security with segmentation, encryption, and DDoS controls, cutting security incidents 40%

• Automated workflow for Murex services, integrated Apache Airflow, and optimized XML rules, propelled task efficiency by 30%

• Led DB migration and schema design for 20+ DataMart DBs, enhancing query efficiency and enabling real-time reporting Sottura Mumbai, India

Software Developer May 2022 - January 2023

• Shipped a Next.js + TypeScript app used by 100K+ users, cutting page load time by 67% via SSR, caching, and bundle optimization

• Enhanced stability and reduced critical bugs by 38% through Agile collaboration and automated testing with Selenium for pipelines

• Improved hot endpoints with Redis caching + rate limiting; cut p95 latency 40% and sustained 1.2k req/s at peak Oasis Infobyte Mumbai, India

Data Analyst January 2022 - May 2022

• Created interactive Tableau and Power BI dashboards, analyzing large-scale datasets to uncover trends and improve decision- making efficiency by 25%

• Designed Python (Pandas, Flask) and SQL data pipelines, enabling high-throughput analytics and reducing downtime by 44%

• Streamlined microservices with centralized logs and alerts handling 1.5M requests/day with faster response times Projects

Intent Grounded Shopping Agent Benchmark (Pydantic, Lang-graph, Langfuse, streamlit) Link March 2026 – Present

• Built an LLM agent benchmark on a 2.5M+ product shopping sandbox, generating rollouts and scoring gt/success/format metrics

• Enabled tool-call governance with allow/block + required-parameter checks, surfaced in a Streamlit dashboard for per-tool compliance auditing

Multi-Agent Learning System (Python, Lang-graph, NeMo, K8, Langfuse, GCP) Link January 2026 – Present

• Executed 10+ multi-agent LLM workflows via LangGraph with traceability using Langfuse, NeMo Guardrails, and Rebuff

• Deployed GCP Pub/Sub, Cloud Run, GKE, and Artifact Registry for efficient scaling, improved load balancing by 23.2% TaskHarbor (AWS, Go, Jest, Pytorch) Link November 2025 – February 2026

• Assembled a Go-based job framework with pluggable drivers, workflows, retries, leases, handling 1000+ concurrent jobs

• Added crash recovery, idempotency, and observability, workflow downtime and increased throughput to 100k events/day Cloud-Clinic (AWS, Hugging Face, Docker, Next.js, Flask) Link September 2025 – January 2026

• Designed an AI chatbot with RAG and vector embeddings from O*NET and BLS, using Crew.ai, revamped accuracy by 47.3%

• Utilized WebRTC, AWS Lambda, and S3 to enable video calls, session management, and secure record sharing for 5+ users Leadership

Graduate Consulting Club New York, NY

President September 2025 – Present

• Led 15+ strategic networking and professional events connecting students with 40+ consulting professionals across industry and alumni networks

• Expanded the club’s employer network by bringing in speakers from JPMorgan and WSFS Bank, engaging 2,000+ students and strengthening alumni recruiting connections.

• Launched a consulting project-sprint program and led cross-functional teams to deliver real-world case solutions Association for Computing Machinery (ACM)

Team-Head January 2025 – September 2025

• Supported 60+ student users on shared compute, standardizing environments and queue practices to cut failed jobs by 30% and improve throughput

• Configured and troubleshot lab network connectivity (TCP/IP, VLANs, routing basics, firewall/VPN access), cutting initial research environment setup effort by 65% and unblocking projects faster. Education

Stevens Institute of Technology Expected May 2026

Master of Science in Computer Science GPA – 4 Hoboken, NJ Relevant Coursework: Cloud Infrastructure, Deep Learning, Agile development methodology, Distributed Systems Mumbai University August 2019 - May 2023

Bachelor of Engineering in Information Technology GPA – 4 Mumbai, India Relevant Coursework: Data Science & Bigdata Analytics, Artificial Intelligence, Machine Learning, Business Intelligence

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