Suraj Mittal
Software Engineer at Adtran
Bengaluru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolSuraj Mittal is a software engineer and DevOps practitioner with a decade of hands-on experience building cloud-native infrastructure, CI/CD pipelines, and observability stacks, currently contributing to scalable solutions at Adtran. His journey from college projects at Dayananda Sagar to industry internships and certifications (AWS, Linux for DevOps, Power BI) underpins a practical focus on IaC, Docker/Kubernetes, Prometheus/Grafana, and GitHub Actions/Jenkins. He pairs systems thinking with automation-first delivery, having progressed from student intern roles to a full-time engineering position within the same company in 2024. An active contributor to open-source ML tooling, he’s fixed critical compatibility and model-saving bugs in the popular flairNLP project, demonstrating attention to cross-environment reliability. Suraj is motivated by challenging problems that tighten the loop between development velocity and production safety, and he prefers hands-on solutions that scale.
11 years of coding experience
1 year of employment as a software developer
School, School at La Martinere CollegeHigh School Diploma, Class 11 and 12, High School Diploma, Class 11 and 12 at City Montessori SchoolBachelor of Engineering - BE, Computer Science, Bachelor of Engineering - BE, Computer Science at Dayananda Sagar College of Engineering, BANGALORE
Github Skills (8)
pytorch10
machine-learning10
nlp10
python10
natural-language-processing10
sequence-labeling9
debugging9
word-embeddings8
Programming languages (10)
Github contributions (5)
flairNLP/flair
Aug 2018 - Feb 2020
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 4 PRs, 10 comments in 1 year 6 months
Contributions summary:Suraj primarily focused on bug fixes and ensuring compatibility with different PyTorch versions within the Flair NLP framework. Their commits address issues related to saving models, particularly when not using a development dataset, and adjusting code to handle variations in PyTorch versions, including those with CPU-only support and version strings with extra characters. They also fixed a bug that prevented the model from saving during training. The modifications directly impact the model's ability to train and be compatible across different environments.
natural-language-processingpytorchnlpnamed-entity-recognitionsequence-labeling
SetuHQ/superset
Feb 2023 - May 2025
Apache Superset is a Data Visualization and Data Exploration Platform
Contributions:1 release, 5 reviews, 10 PRs in 2 years 2 months
apache-supersetdata-explorationdata-visualizationsuperset
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