Deren Singh, Developer in Boston, MA, United States
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Deren Singh

Artificial Intelligence Engineer and Developer

Boston, MA, United States

Toptal member since February 24, 2026

Bio

Deren is an AI engineer who turns cutting-edge LLM research into production-ready systems that scale. With deep expertise in Kubernetes, AWS, and distributed training orchestration, he architects inference pipelines that maintain over 99.9% availability across multi-region deployments. From building intelligent AI agent systems with MCP and FastMCP to designing robust MLOps workflows, Deren delivers enterprise solutions that drive measurable business impact.

Portfolio

Slingshot Aerospace
Python, Artificial Intelligence (AI), CI/CD Pipelines, MLflow, Machine Learning...
National Grid
Python, Databricks, CI/CD Pipelines, Data Engineering, SQL, Snowflake...
FlightLevel Technologies
Python, Computer Vision, Artificial Intelligence (AI), Object Detection, YOLOv5...

Experience

  • Python - 15 years
  • Databricks - 6 years
  • Artificial Intelligence (AI) - 5 years
  • Machine Learning Operations (MLOps) - 4 years
  • Large Language Models (LLMs) - 4 years
  • Kubernetes - 4 years
  • AI Engineering - 3 years
  • AI Agents - 2 years

Preferred Environment

Artificial Intelligence (AI), Machine Learning Operations (MLOps), AI Engineering

The most amazing...

...project I've developed is an AI agent platform using MCP that autonomously orchestrated multi-agent workflows, transforming how an enterprise operated at scale.

Work Experience

MLOps Specialist

2025 - PRESENT
Slingshot Aerospace
  • Designed and deployed end-to-end pipelines for custom LLM applications with advanced MLOps practices.
  • Architected LLM inference systems on AWS and Kubernetes with over 99.9% availability.
  • Implemented automated canary releases and rollbacks across multi-region deployments.
  • Built CI/CD pipelines with automated testing frameworks to accelerate iteration and reduce risk.
  • Orchestrated distributed training workflows integrating Anyscale Ray clusters with production environments.
  • Developed advanced AI agent systems using agent-to-agent interaction, MCP, and FastMCP.
  • Implemented MLflow for experiment tracking, model registry, and lifecycle management.
Technologies: Python, Artificial Intelligence (AI), CI/CD Pipelines, MLflow, Machine Learning, Kubernetes, Automated Testing, Databricks, Model Context Protocol (MCP), AI Agents, Large Language Models (LLMs), Machine Learning Operations (MLOps), Distributed Computing, Azure Databricks, Docker, Large Language Model Operations (LLMOps), AWS Deployment, Automation, AWS DevOps, Amazon Web Services (AWS), Infrastructure, DevOps, LangChain, LangGraph, Retrieval-augmented Generation (RAG), Agentic RAG Systems, RAG Pipelines, Vector Databases, Natural Language Processing (NLP), SQL, Natural Language Queries, Natural Language Understanding (NLU), Data Engineering, Analytics, Dashboards, Data Analytics, Image Generation, 3D, Diffusion Models, JavaScript, AI Design, AI Programming, Google Cloud Platform (GCP), Gemini Enterprise, Agentic AI, Data Science, AI Engineering, RAG Architecture, PySpark, ETL, Microsoft Dynamics, Data Visualization, Amazon Bedrock, Anthropic, RAG Systems, Generative Artificial Intelligence (GenAI), OpenAI, Prompt Engineering, NumPy, Pandas

Data Engineer

2023 - 2025
National Grid
  • Architected a modern data framework using Databricks, empowering eight engineering teams.
  • Orchestrated end-to-end ETL cycles leveraging Snowflake, SQL, Python, and Azure SQL Database/Server.
  • Optimized Databricks environments through expert configuration of jobs, workflows, pipelines, and clusters.
  • Implemented CI/CD pipelines via GitHub Actions for enhanced version control and deployment.
  • Established data-lake best practices that foster centralized storage and a data-driven culture.
  • Leveraged Databricks Asset Bundles to boost code modularity and reusability across projects.
Technologies: Python, Databricks, CI/CD Pipelines, Data Engineering, SQL, Snowflake, Azure Databricks, Automation, Infrastructure, DevOps, Analytics, Dashboards, Data Analytics, JavaScript, Data Science, PySpark, ETL, Microsoft Dynamics, Data Visualization, NumPy, Pandas

Founder & Lead Developer

2022 - 2025
FlightLevel Technologies
  • Pioneered an industry-transforming aviation navigation platform from the ground up.
  • Architected real-time data processing systems that set new standards for visualization and performance.
  • Forged strategic partnerships with Nvidia, Microsoft, Google, and other tech leaders.
  • Implemented Azure Cloud Services for scalable cloud infrastructure.
  • Built YOLO computer vision and object reidentification algorithms for exceptional system accuracy.
  • Maintained over 99.9% uptime while enforcing rigorous security protocols.
  • Led the company to a successful acquisition by FlightLevel Aviation in 2022.
Technologies: Python, Computer Vision, Artificial Intelligence (AI), Object Detection, YOLOv5, IP Cameras, Optics, PTZ Cameras, Cloud, Content Delivery Networks (CDN), Azure Databricks, Docker, Snowflake, AI Agents, Machine Learning, Kubernetes, Machine Learning Operations (MLOps), AWS Deployment, Automation, AWS DevOps, Amazon Web Services (AWS), Infrastructure, DevOps, LangChain, Retrieval-augmented Generation (RAG), Agentic RAG Systems, RAG Pipelines, Vector Databases, SQL, Data Engineering, Analytics, Dashboards, Data Analytics, Tableau, Financial Data, Image Generation, 3D, Diffusion Models, JavaScript, AI Design, AI Programming, Google Cloud Platform (GCP), Vertex AI, Gemini Enterprise, Agentic AI, Data Science, AI Engineering, RAG Architecture, PySpark, ETL, Microsoft Dynamics, Data Visualization, Anthropic, RAG Systems, Generative Artificial Intelligence (GenAI), OpenAI, Prompt Engineering, NumPy, Pandas

Cloud Developer

2020 - 2022
National Grid
  • Designed, developed, and sustained multiple Microsoft Azure cloud deployments for global business units.
  • Architected secure virtual networks for internet/intranet applications with specific subnets for deployment.
  • Led cloud governance by addressing subscriptions, configurations, and utilization across Azure tenants.
  • Built infrastructure as code using Ansible and Terraform for repeatable, reliable deployments.
  • Applied full SDLC practices, including Agile sprints, Kanban boards, peer code reviews, automated builds, pipelining, testing, and CI/CD.
Technologies: Azure, Azure Compute Services, Azure SQL, Microsoft Azure Cloud Server, Azure SQL Databases, Serverless, Redis, Cloud Security, Ansible, Terraform, Infrastructure, Infrastructure as Code (IaC), Virtual Machines, Azure Virtual Machines, DevSecOps, Data Engineering, Analytics, Dashboards, Data Analytics, PySpark, ETL, Microsoft Dynamics, Data Visualization, Pandas

Software Development Engineer

2019 - 2020
Amazon Web Services (AWS)
  • Built scalable database infrastructure with Amazon Aurora. Developed and managed databases and clusters across global regions, supporting critical business operations at scale.
  • Implemented a comprehensive unit testing system for Aurora clusters, significantly improved code reliability, ensured the integrity of database operations, and reduced downtime.
  • Designed and developed dynamic web applications. Built apps using REST, HTML, CSS, and JavaScript, integrating data via APIs to enhance user experience and functionality.
  • Contributed to CI/CD pipeline practices. Ensured continuous integration and deployment of code changes, enabling high-quality software delivery in a fast-paced environment.
  • Applied professional Agile and DevSecOps practices. Participated in sprints, code reviews, coding standards enforcement, and source control management across the development lifecycle.
Technologies: Java, Amazon Aurora, AWS IoT, REST, HTML, CSS, JavaScript, CI/CD Pipelines, Unit Testing, DevSecOps, Data Engineering, Data Analytics

Experience

Aircraft Camera Tracker

Built a real-time aircraft tracking system using PTZ (pan-tilt-zoom) cameras powered by custom computer vision pipelines.

I leveraged YOLO object detection and reidentification algorithms to autonomously detect, lock onto, and track aircraft across the sky with high precision. The system dynamically adjusted pan, tilt, and zoom coordinates in real time based on predicted flight trajectories, enabling seamless continuous tracking without manual operator intervention.

I also engineered low-latency data processing pipelines on Azure Cloud Services to handle high-throughput video streams, ensuring reliable performance under varying weather and lighting conditions. The solution became a core component of FlightLevel's aviation navigation platform, delivering exceptional accuracy and directly contributing to the platform's industry-leading visualization capabilities.

Openpyxl-Rust

https://github.com/derens99/openpyxl-rust
An open-source, high-performance Excel (.xlsx) writer library that provides a drop-in replacement for Python's openpyxl, powered by a Rust back end. It mirrors openpyxl's familiar Python API while storing cell data in Rust memory via PyO3 and using rust_xlsxwriter for file serialization, achieving 2-3x faster write performance on large workbooks. Supports a comprehensive feature set including styling, images, data validation, conditional formatting, merged cells, sheet protection, and more.

rjson

rjson is a Rust-backed drop-in replacement for Python's stdlib json module. Unlike orjson (which returns bytes, lacks JSONEncoder subclassing, and has a different API), rjson achieves 100% behavioral compatibility with import json while delivering Rust-level performance.

Education

2024 - 2026

Master's Degree in Business Administration

University of Massachusetts Lowell - Lowell, MA, USA

2017 - 2021

Bachelor's Degree in Computer Science

Boston University - Boston, MA, USA

Certifications

JUNE 2024 - PRESENT

Microsoft Certified: Azure Data Fundamentals

Microsoft

MAY 2024 - PRESENT

Azure Databricks Platform Architect

Databricks

Skills

Libraries/APIs

PySpark, NumPy, Pandas, ExcelJS

Tools

AWS Deployment, Terraform, Tableau, Microsoft Dynamics, Ansible

Languages

Python, SQL, JavaScript, Snowflake, Java, HTML, CSS, Rust

Frameworks

LangGraph

Paradigms

Model Context Protocol (MCP), Automation, DevOps, ETL, Automated Testing, Distributed Computing, REST, Unit Testing, DevSecOps

Platforms

Kubernetes, Databricks, Docker, Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Vertex AI, AWS IoT

Storage

Amazon Aurora, Azure SQL, Azure SQL Databases, Redis

Other

Artificial Intelligence (AI), CI/CD Pipelines, Machine Learning, AI Agents, Large Language Models (LLMs), Machine Learning Operations (MLOps), Data Engineering, Azure Databricks, AI Engineering, Large Language Model Operations (LLMOps), AWS DevOps, Infrastructure, LangChain, Retrieval-augmented Generation (RAG), Agentic RAG Systems, RAG Pipelines, Vector Databases, Natural Language Processing (NLP), Natural Language Queries, Natural Language Understanding (NLU), Analytics, Dashboards, Data Analytics, Financial Data, Image Generation, 3D, Diffusion Models, AI Design, AI Programming, Gemini Enterprise, Agentic AI, Data Science, RAG Architecture, Data Visualization, Amazon Bedrock, Anthropic, RAG Systems, Generative Artificial Intelligence (GenAI), OpenAI, Prompt Engineering, Business, MLflow, Computer Vision, Object Detection, YOLOv5, IP Cameras, Optics, PTZ Cameras, Cloud, Content Delivery Networks (CDN), Azure Data Lake, Azure Compute Services, Microsoft Azure Cloud Server, Serverless, Cloud Security, Infrastructure as Code (IaC), Virtual Machines, Azure Virtual Machines, API Design, Open Source, Memory Management

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