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Pranav Sateesh

Tech Lead @ Transcality

Zürich Metropolitan Area

7+ years of work experience

Transcality
Jul 20233 yrs 4 mosPresent

Zurich, Switzerland

I lead the technical platform behind Transcality's digital-twin traffic products, PLAN and OPERATE covering realtime and long term planning products. Platform & cloud: AWS (EKS, ECS Fargate, Step Functions), infrastructure-as-code (OpenTofu), multi-tenant architecture + on-premises CI/CD cutting hosting costs & optimisation Distributed compute: massively parallel SUMO simulation on Kubernetes, scale-to-zero autoscaling, 15-minute operational SLA GPU & numerical engineering: reformulation of cpu pipelines with CUDA solvers; building a differentiable traffic simulator Data & security: geospatial pipelines, provenance-tracked Parquet, multi-tenancy, SSO/MFA, SOC 2 readiness
Indian Institute of Technology, Madras
Aug 20192 yrs 1 moAug 2021

Greater Chennai Area

1. Working on Spin Echo signal simulations on QuTip (Quantum toolbox in python) and its application for analyzing Hahn Echo signals, Rabi Oscillations under Professor Praveen Bhallamudi, Physics Department, IIT Madras. 2. Working on my Bachelor's Thesis on Non-Linear control of quantum defects for application in quantum computing
Indian Institute of Technology, Madras
May 20194 mosAug 2019

Greater Chennai Area

Worked on simulating quantum systems namely, Jaynes-Cummings model and also analysis of NV-Centers using QuTip (Quantum toolbox in python) under Professor Praveen Bhallamudi, Physics Department, IITM.
Freelance
Mar 20193 y 11 moFeb 2023

Bengaluru, Karnataka, India

BosonQ-PSI 3-D Computation & Visualisation • Devised optimisation maths and precision controls for engineering-scale models on BQP’s web platform. • Built custom Three.js + WebAssembly/Rust loaders and a C++/Python converter, cutting memory 25 %, boosting accuracy 10 %, and halving load times. FactorResearch Quantitative Analytics • Engineered Python back-test engines for long-short and factor strategies across global equities, bonds, and commodities. • Accelerated pipelines with Modin, multiprocessing, NumPy/Pandas; fine-tuned models via RNN/LSTM (TensorFlow/Keras) and authored strategy white papers for institutional clients. Fabrik High-Performance Graphics Tooling • Designed proprietary image-processing and path-finding algorithms for circuit-analysis tooling; created mathematical optimisation routines for multilayer systems; • Created deployable model-format converters with vertex-reduction (C++/Rust) and fast WebAssembly loaders, enabling seamless CAD ↔ WebGL for quicker loads. Algo One AI Proprietary Trading R&D • Modelled technical + fundamental signals to design long / semi-long U.S. equity strategies. • Applied intensive data-mining, fine-tuned models via RNN/LSTM (TensorFlow/Keras), back-testing, and deep-learning optimisation to raise risk-adjusted returns. Full-Stack & DevOps (Fabrik, BQP, others) • Delivered production apps with Angular/React/Three.js front ends and Node/Django back ends. • Set up CI/CD, containerised services, and orchestrated AWS (EC2, EKS, Lambda, S3) to sustain > 99 % uptime. PillarPlus Algorithmic & Data-Science Solutions • Devised algorithms to estimate costs from floor-plan images. • Redesigned and optimized component matching pipeline, resulting in a 66% reduction in detection time. Core tech & skills: Python, C++, Rust, WebAssembly, Three.js, TensorFlow/Keras, NumPy/Pandas/Modin, Plotly, AWS, CI/CD, Optimisation, Scalability, Quantitative Modelling, Image Processing, Mesh Algorithms.
Indian Institute of Technology, Madras
Dec 20182 mosJan 2019

Greater Chennai Area

• Developed comprehensive mathematical models using Python (Numpy, Scipy) and MATLAB to analyze fluid droplet dynamics in different mediums, showcasing strong problem-solving abilities. • Investigated the dynamics of fluid droplets utilizing PDE solvers, making notable contributions to the field of fluid mechanics. • Leveraged mathematical models to explore the Landau-Lifshitz formula, delving into the fundamental aspects of material science.
GitHub
@stprnvsh

Pranav’s AI Stack

claude code
claude code
claude
claude
mcp
mcp
mistral
mistral

Education

USI Università della Svizzera italiana

Master of Science - MS, Computational Science

USI Università della Svizzera italiana

Shiv Nadar University

Bachelor of Science - BS, Physics

Shiv Nadar University

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Pranav Sateesh on Tal

Headline

Tech Lead @ Transcality

About

Quantitative researcher turned platform engineer. 8+ years turning mathematical models into production systems across scientific computing, ML, finance, and physics. Currently Tech Lead at Transcality I own the platform behind city-scale traffic digital twins, from AWS/Kubernetes infrastructure and massively parallel simulations to GPU-native numerical solvers

Location

Zürich Metropolitan Area

AI stack

claude code

claude

mcp

mistral

Work experience

Technical Lead at Transcality, Jul 2023 - Present · 3 yrs 4 mos, Zurich, Switzerland, I lead the technical platform behind Transcality's digital-twin traffic products, PLAN and OPERATE covering realtime and long term planning products. Platform & cloud: AWS (EKS, ECS Fargate, Step Functions), infrastructure-as-code (OpenTofu), multi-tenant architecture + on-premises CI/CD cutting hosting costs & optimisation Distributed compute: massively parallel SUMO simulation on Kubernetes, scale-to-zero autoscaling, 15-minute operational SLA GPU & numerical engineering: reformulation of cpu pipelines with CUDA solvers; building a differentiable traffic simulator Data & security: geospatial pipelines, provenance-tracked Parquet, multi-tenancy, SSO/MFA, SOC 2 readiness

Researcher at Indian Institute of Technology, Madras, Aug 2019 - Aug 2021 · 2 yrs 1 mo, Greater Chennai Area, 1. Working on Spin Echo signal simulations on QuTip (Quantum toolbox in python) and its application for analyzing Hahn Echo signals, Rabi Oscillations under Professor Praveen Bhallamudi, Physics Department, IIT Madras. 2. Working on my Bachelor's Thesis on Non-Linear control of quantum defects for application in quantum computing

Summer Intern at Indian Institute of Technology, Madras, May 2019 - Aug 2019 · 4 mos, Greater Chennai Area, Worked on simulating quantum systems namely, Jaynes-Cummings model and also analysis of NV-Centers using QuTip (Quantum toolbox in python) under Professor Praveen Bhallamudi, Physics Department, IITM.

Consulting Engineer at Freelance, Mar 2019 - Feb 2023 · 3 y 11 mo, Bengaluru, Karnataka, India, BosonQ-PSI 3-D Computation & Visualisation • Devised optimisation maths and precision controls for engineering-scale models on BQP’s web platform. • Built custom Three.js + WebAssembly/Rust loaders and a C++/Python converter, cutting memory 25 %, boosting accuracy 10 %, and halving load times. FactorResearch Quantitative Analytics • Engineered Python back-test engines for long-short and factor strategies across global equities, bonds, and commodities. • Accelerated pipelines with Modin, multiprocessing, NumPy/Pandas; fine-tuned models via RNN/LSTM (TensorFlow/Keras) and authored strategy white papers for institutional clients. Fabrik High-Performance Graphics Tooling • Designed proprietary image-processing and path-finding algorithms for circuit-analysis tooling; created mathematical optimisation routines for multilayer systems; • Created deployable model-format converters with vertex-reduction (C++/Rust) and fast WebAssembly loaders, enabling seamless CAD ↔ WebGL for quicker loads. Algo One AI Proprietary Trading R&D • Modelled technical + fundamental signals to design long / semi-long U.S. equity strategies. • Applied intensive data-mining, fine-tuned models via RNN/LSTM (TensorFlow/Keras), back-testing, and deep-learning optimisation to raise risk-adjusted returns. Full-Stack & DevOps (Fabrik, BQP, others) • Delivered production apps with Angular/React/Three.js front ends and Node/Django back ends. • Set up CI/CD, containerised services, and orchestrated AWS (EC2, EKS, Lambda, S3) to sustain > 99 % uptime. PillarPlus Algorithmic & Data-Science Solutions • Devised algorithms to estimate costs from floor-plan images. • Redesigned and optimized component matching pipeline, resulting in a 66% reduction in detection time. Core tech & skills: Python, C++, Rust, WebAssembly, Three.js, TensorFlow/Keras, NumPy/Pandas/Modin, Plotly, AWS, CI/CD, Optimisation, Scalability, Quantitative Modelling, Image Processing, Mesh Algorithms.

Winter Intern at Indian Institute of Technology, Madras, Dec 2018 - Jan 2019 · 2 mos, Greater Chennai Area, • Developed comprehensive mathematical models using Python (Numpy, Scipy) and MATLAB to analyze fluid droplet dynamics in different mediums, showcasing strong problem-solving abilities. • Investigated the dynamics of fluid droplets utilizing PDE solvers, making notable contributions to the field of fluid mechanics. • Leveraged mathematical models to explore the Landau-Lifshitz formula, delving into the fundamental aspects of material science.

Education

Master of Science - MS, Computational Science, USI Università della Svizzera italiana

Bachelor of Science - BS, Physics, Shiv Nadar University

Public links

github: https://github.com/stprnvsh

Pranav Sateesh - Technical Lead in Zürich Metropolitan Area | Tal