Work Experience

• AI Simulation Engineer (Jan 2025 – March 2026)
  Huawei
  Helsinki, Finland
  • Technical project planning, proposal, and execution for consumer electronics devices, next generation battery technology.
  • Develop AI and simulation technologies by integrating physics-based models with data-driven, transfer-learning and physics-informed machine learning approaches to improve characterization of consumer electronics devices and hybrid simulation approaches
  • Advance lithium-ion battery research for consumer electronics by characterizing new cell technologies, modeling degradation mechanisms, and supporting improvements in online battery management systems.
  • Built AI‑based characterization tools to analyze device behavior, performance patterns, and system reliability.
  • Improved online Battery Management Systems (BMS) by developing predictive algorithms for SOH, aging, and performance.
  • Designed simulation workflows combining physics‑based models with ML to enhance accuracy and reduce testing cycles.
  • Collaborated with cross‑functional engineering teams to translate simulation insights into product improvements and design decisions.
• AI Engineer (Oct 2024 – Dec 2024)
  Digi Energia Oy
  Helsinki, Finland
  • Designed and deployed AI‑driven payment intelligence to improve transaction security, automate billing, and reduce fraud across EV charging networks.
  • Built predictive ML models for pricing, demand forecasting, and customer behavior to support real‑time operational decisions.
  • Integrated AI services across payment systems and charger IoT platforms, ensuring seamless data flow and optimized system performance.
  • Developed end‑to‑end ML pipelines, from data processing to model deployment, supporting scalable FinTech and EV charging applications.
  • Collaborated with engineering, product, and operations teams to embed AI capabilities into core business workflows.
  • Monitored and improved model accuracy, ensuring high‑quality data, reliable predictions, and continuous system enhancement.
• Senior Software Engineer (Mar 2023 – Sept 2024)
  VALT
  Milton Keynes, England, United Kingdom
  • Developed complex, scalable REST APIs using NodeJS, Python, FastAPI, PostgreSQL, MongoDB, and Redis for high‑performance payment and EPOS systems.
  • Integrated Stripe payment workflows, building secure custom payment handlers and automated billing pipelines.
  • Designed and deployed ML solutions for core product intelligence, including pricing, recommendations, and operational automation.
  • Built and optimized cloud‑native architectures on AWS and GCP using Lambda, EC2, Airflow, caching layers, and containerized services.
  • Implemented CI/CD pipelines with GitLab and Git to ensure fast, reliable, and automated deployments.
  • Developed scalable data pipelines to support analytics, model training, and real‑time decision systems.
  • Collaborated with cross‑functional teams, including mobile, frontend, and product, to deliver end‑to‑end features.
  • Improved system performance and reliability through caching strategies, API optimization, and distributed service design.
• AI Engineer (Jan 2023 – Mar 2023)
  Carbarn
  Sydney, New South Wales, Australia
  • Developed and maintained AI/ML models for pricing, demand forecasting, customer recommendations, and marketplace optimization.
  • Built and improved search, ranking, and recommendation algorithms to enhance car‑buying and discovery experiences.
  • Collected and analyzed competitor data using automated web‑scraping tools (BeautifulSoup, Scrapy, Selenium) to support strategic decisions.
  • Processed and transformed large datasets with Airflow and Spark to generate insights for sales, marketing, and product teams.
  • Collaborated with cross‑functional teams to integrate AI solutions into business workflows and customer‑facing features.
  • Monitored model performance and data quality, ensuring continuous accuracy, reliability, and improvement of AI systems.
• Lead Software Engineer (Dec 2019 – Dec 2022)
  Ordervox
  London, England, United Kingdom
  • Led full‑stack development of scalable web, mobile, and desktop applications using Python, PHP, FastAPI, JavaScript, Java, and CodeIgniter for the OrderE restaurant automation platform.
  • Architected and optimized cloud infrastructure across AWS Lambda, EC2, ECS, RDS, Redis, Docker, and Kubernetes to support high‑traffic operations for 300+ restaurant clients.
  • Designed cost‑efficient backend systems and data pipelines, improving automation, performance, and reliability across ordering, delivery, and in‑house dining workflows.
  • Managed an 8‑member core engineering team, driving agile execution, sprint planning, code quality, and on‑time delivery of complex product features.
  • Enhanced system performance and scalability through caching strategies, PL/SQL optimization, and cloud‑native best practices to ensure a seamless customer experience.
• Software Engineer Intern (Jan 2018 – Dec 2019)
  Parking koi INC
  Dhaka, Bangladesh
  • Implemented and maintained Google Maps–based location and routing features for a car‑parking solution (Uber‑style), building RESTful APIs using PHP, CodeIgniter, JavaScript, and AJAX.
  • Deployed and supported backend services on AWS, ensuring reliable performance, version control, and smooth feature delivery using Git.
  • Integrated map interactions such as distance calculation, live position updates, and dynamic marker rendering for smooth user experience.
  • Deployed backend services on AWS, ensuring stable performance, uptime, and secure environment configuration.
  • Collaborated using Git for version control, contributing to feature development, bug fixes, and code reviews within the engineering team.

Skills

• Languages: English (C1), Finnish (A2)
• Programming/Framework: Python, Javascript, PHP, NodeJs, Shell, Postgre-SQL, C, C++, MySQL, Mongodb, Git, FastApi, Django, Codeigniter, RestAPI, CSS, Docker, Kubernetes
• ML: MLflow, PyTorch, FastAPI, PyTorch, TensorFlow, Keras, and Scikit-Learn for computer vision, NLP, LLMs, MLOps, Airflow, and CI/CD (GitHub Actions, GitLab), (Most of ML model implementation)
• Generative AI: Designed, fine-tuned, and deployed LLM and RAG-based applications, tokenization, vector search
• Data Science: feature engineering, Snowflake, Spark, BeautifulSoup, Scrapy, Selenium, Azure Data Engineering tools, Data-bricks, PowerBI
• Research: Overleaf, Lucidchart, Matlab, LaTeX, Rails, OCaml
• Document Creation: Microsoft Office Suite, LaTex, Overleaf, Lucidchart