Suchindu Malith
@suchindu · 2026

Suchindu
Malith

Data Science Undergraduate · Aspiring MLOps Engineer

Enthusiastic and research-driven data science student at SLIIT, passionate about building scalable ML pipelines, intelligent systems, and bridging the gap between model development and production engineering.

suchindump@gmail.com +94 71 480 8366 linkedin.com/in/suchindu github.com/suchindu
Languages & Frameworks
Python R SQL Java TensorFlow Scikit-learn Flask Pandas
Data Engineering & BI
SQL Server SSIS SSAS Power BI Snowflake SSRS OLAP
Cloud & DevOps
AWS Azure Docker Kubernetes Terraform Linux Nginx
AI / ML Specialisation
Machine Learning Deep Learning NLP MLOps n8n Opensearch
01

Introduction

I am Suchindu Malith, a final-year undergraduate at the Sri Lanka Institute of Information Technology (SLIIT), specialising in Data Science under the BSc (Hons) in Information Technology programme. My academic journey has been shaped by a deep curiosity about the intersection of data, machine learning, and scalable systems engineering.

My core interest lies in MLOps — the discipline that brings machine learning models from research notebooks into reliable, monitored, production-grade systems. I am drawn to the engineering challenges of model versioning, automated retraining pipelines, container orchestration, and cloud deployment, and I actively build projects that reflect these interests.

Beyond technical skills, I value clear communication, collaborative problem-solving, and a research-driven mindset. I am a member of both IEEE EMBS and SEDS at SLIIT, where I have taken on leadership roles that have sharpened my project management and team coordination abilities.

My education at SLIIT has given me a strong foundation in statistics, algorithms, and software engineering — and the PPW module has deepened my awareness of the professional communication skills needed to succeed in the industry.

4+
Production-grade ML projects deployed
2
Cloud certifications earned (AWS & Google AI)
IEEE
Asst. Secretary — IEEE EMBS SLIIT Chapter
SEDS
Divisions Manager, SEDS SLIIT
03

Career Development Plan

My long-term career goal is to become a Machine Learning Operations (MLOps) Engineer — someone who bridges the gap between data science research and scalable, reliable production systems. This is where my technical passions converge: machine learning, cloud infrastructure, containerisation, and automation.

The roadmap below outlines the progression I intend to follow, building both technical depth and professional breadth at each stage.

Self-Assessment

Strengths: Strong Python and ML foundations, hands-on data engineering experience (SSIS, SSAS, Power BI), cloud exposure (AWS, Azure, Docker, Kubernetes), research-driven learning style, leadership through IEEE and SEDS.

Areas for Growth

To develop: Production MLOps tooling (MLflow, Kubeflow, Airflow), advanced CI/CD pipeline configuration, real-world model monitoring and drift detection, and stronger communication of technical work to non-technical audiences.

Short-term · 0–1 year

Foundation & Certification

Complete BSc (Hons) degree with a strong GPA at SLIIT
Obtain AWS Solutions Architect Associate or MLOps certification
Build and deploy an end-to-end MLOps pipeline project (MLflow + Docker + GitHub Actions)
Contribute to an open-source ML or data engineering project
Improve professional communication, documentation, and report writing skills (via PPW)
Medium-term · 1–3 years

Junior to Mid-Level MLOps Engineer

Secure a junior data engineering or MLOps engineer role at a product-led tech company
Work with Kubeflow, Airflow, or Prefect in production environments
Implement model monitoring, A/B testing infrastructure, and retraining triggers
Gain experience with feature stores and vector databases
Build visibility through technical blog posts and conference participation
Long-term · 3–7 years

Senior MLOps Engineer / ML Platform Lead

Lead the design of organisation-wide ML platforms and infrastructure
Pursue a postgraduate qualification in AI/ML Engineering or Systems
Mentor junior engineers and data scientists
Speak at data/AI engineering conferences (PyCon, KubeCon, MLconf)
Explore founding or contributing to a data-infrastructure startup
04

Curriculum Vitae

Education
Sri Lanka Institute of Information Technology 2022 – Present
BSc (Hons) in Information Technology — Specialised in Data Science

Malabe, Sri Lanka

St. Thomas' College 2019
G.C.E. Advanced Level — Physical Science

Combined Maths: A · Physics: C · Chemistry: C — Matara, Sri Lanka

Technical Skills
  • Languages: Python, R, Java, JavaScript, C, HTML, CSS, SQL
  • Frameworks & Libraries: TensorFlow, Scikit-learn, Flask, MERN Stack, Pandas, NumPy, n8n
  • Data Engineering: SQL Server, SSIS, SSAS, Snowflake Schema, Data Warehousing, OLAP, MySQL
  • BI & Visualisation: Power BI, SSRS, Excel (PivotTables, Power Query), Matplotlib
  • Cloud & DevOps: AWS, Azure, Docker, Kubernetes, Terraform, Ansible, Nginx, Linux
  • Developer Tools: Git, Figma, Opensearch, Power Automate, VS Code, Jupyter Notebook
  • Concepts: ML, Deep Learning, NLP, Big Data, Agile, OOP, Data Structures & Algorithms
Certifications
Cloud Foundation — AWS Academy Oct 2024
Google AI Essentials — Google Aug 2025
Extra-Curricular & Volunteering
IEEE EMBS SLIIT Jan 2024 – Present
Assistant Secretary
  • SliitXtreme 2.0 – Program Team
  • Aureus '24 – Finance Team
  • Skills: Project Management, Event Coordination, Analysis & Reporting
SEDS SLIIT Jan 2024 – Present
Divisions Manager
  • Event Chair – Awareness Session '24
  • Skills: Leadership, Team Management, Strategic Decision-Making
Soft Skills
  • Team Collaboration & Cross-functional Communication
  • Adaptive Behaviour & Continuous Learning
  • Strategic Planning & Time Management
  • Data Storytelling — presenting findings to non-technical audiences
Languages
  • English — Advanced (reading, writing, speaking)
  • Sinhala — Native
References
Mr. Nuwan Chamara
Senior Network Engineer, NTT DATA Singapore

nuwan.chamara@global.ntt · +94 77 748 9384

Mr. Samadhi Chathuranga Rathnayake
Lecturer, Faculty of Computing, SLIIT

samadhi.r@sliit.lk · +94 71 467 2084

05

Selected Projects

Feb 2025

Data Warehousing Pipeline

End-to-end data integration and analytics solution including ETL processes with SSIS, Snowflake schema-based warehousing, OLAP cube deployment via SSAS for multidimensional analysis, and interactive Power BI and SSRS dashboards for data-driven decision-making.

SSIS SQL Server Snowflake Schema SSAS Power BI SSRS ETL OLAP
Sept 2024

LoanDrive — Loan Default Prediction

Loan default prediction model using SVM and Random Forest with Grid Search optimisation. Includes rigorous data preprocessing, evaluation using precision, recall, and F1-score, and real-time deployment via Streamlit for interactive predictions.

Python Scikit-learn Streamlit SVM Random Forest Jupyter
Oct 2024

Text Summarisation System

Secure web application for text summarisation and analysis using Flask, Hugging Face Transformers, and KeyBERT. Features user authentication, PDF processing, and multiple NLP capabilities including keyword extraction and sentiment analysis.

Python Flask Hugging Face KeyBERT NLP PDF Processing
Dec 2024

Alzheimer's MRI Classification

Deep learning system for Alzheimer's MRI classification using TensorFlow and Flask, enabling real-time dementia stage prediction via image preprocessing and REST API integration. Demonstrates expertise in medical imaging and DL deployment.

TensorFlow Flask Deep Learning Image Processing REST API Python
06

Certifications

WSO2 Certificate — Linux Systems Administration and DevOps Engineering WSO2 Certificate topics covered
MOST RELEVANT · WSO2

Linux Systems Administration & DevOps Engineering

Issued by WSO2 on 06 March 2026. Signed by Sanjiva Weerawarana, Ph.D. (Founder & CEO) and Yasith Nakalanda (Senior Director / Chief Information Officer).

This intensive training programme covered the full DevOps and Linux systems engineering stack — topics directly aligned with my goal of becoming an MLOps Engineer:

  • Linux Administration and Troubleshooting
  • Virtualization (QEMU) and Containerization (Docker)
  • Introduction to Kubernetes
  • Infrastructure as Code — Terraform and Pulumi
  • Log Management with OpenSearch
  • Configuration Management and Automation with Ansible
  • Platform Engineering and Building Platforms
  • Zero Trust Architecture, IAM, Security Concepts
  • Business Continuity and Disaster Recovery

Container orchestration, IaC, and platform engineering are the backbone of production ML systems. This certification proves hands-on capability in the exact tools MLOps engineers use daily in enterprise environments.

WSO2 Certifications · 06.03.2026 · Physical certificate issued
🤖

Google AI Essentials

Issued August 2025

Google

Google AI Essentials Certificate

This certification from Google covers the foundational concepts and practical applications of artificial intelligence, including generative AI principles, prompt engineering techniques, AI ethics and responsible use, and how to evaluate and integrate AI tools into real-world workflows.

Completing this course deepened my understanding of AI not only as a developer but as a practitioner who needs to explain and apply these tools responsibly in a team setting — a key skill for any MLOps engineer bridging research and production.

Google · Aug 2025 · Verified credential
☁️

AWS Cloud Foundation

Issued October 2024

AWS Academy

AWS Academy Cloud Foundation

Validates core knowledge of cloud computing concepts, AWS infrastructure, and core services including compute, storage, networking, and databases. Establishes a solid understanding of the AWS global infrastructure and the shared responsibility model.

Cloud platforms — particularly AWS SageMaker, ECS, and S3 — are central to modern ML deployment pipelines. Understanding cost optimisation, IAM security, and service selection directly informs how I architect ML systems at scale.

AWS Academy · Oct 2024 · Verified credential