Abhishek Saikia

Systems and Software Developer

India
abhisheksaikia766@gmail.com • +91 700-264-3704 • https://linkedin.com/in/abhishek-saikia-268832279
Abhishek Saikia

About

Junior Developer with a passion for building systems and applications. Currently seeking opportunities to further develop my skills in a professional setting.

Education

    Jorhat Engineering College

    Jorhat Engineering College

    Computer Science

Experience

  • -

    Lucknow, Uttar Pradesh - Remote

    Summary:

    • Developing and maintaining web applications using Next.js, Scss, and HTML. Collaborating with the team to implement new features and fix bugs.

    Responsibilities:

    • Built and optimized production-grade UIs using Next.js, Redux, improving load time by about 20% through code-splitting, memoization and SSR tuning.
    • Integrated automated mailing workflows using Nodemailer and Node.js, reducing manual overhead in onboarding flows and improving user activation roles.
    • Designed REST API workflows and Redux state management, cutting client-side response latency by about 15% and ensuring responsive UIs across all viewports using SCSS and Tailwind CSS.

    Achievements:

    • Resolved 50+ bugs and Git merge conflicts, improving stability across CI/CD build pipelines using structured branching workflows.
    • Collaborated in Agile/Scrum sprints with design and backend teams to ship 6+ production features in TypeScript to 1K+ active users.
    • Next
    • React
    • Tailwind
    • Git
    • Scss
  • -

    Silchar, Assam - Remote

    Summary:

    • Using BioBERT, a pretrained biomedical language representation model for biomedical text mining, to understand the symptoms of patients and predict the disease.

    Responsibilities:

    • Built a disease prediction model using NLP (TF-IDF, tokenization) and classification algorithms (Random Forest,SVM) in Python with scikit-learn, achieving 98% validation accuracy.
    • Developed a doctor recommendation engine using cosine similarity on patient symptom vectors, improving match precision over keyword-based filtering.
    • Built Python backend services for model inference, data preprocessing, and real-time prediction APIs using Flask.
    • Python
    • Flask
    • JavaScript
    • Git

Open-Source

  • PR - #2093

    Summary:

    • Identified an observability gap: Athens exposed HTTP-level OpenCensus metrics but lacked proxy-layer cache and upstream fetch metrics, limiting operator visibility into cache effectiveness and upstream reliability.

    Contributions:

    • Implemented three additive OpenCensus metrics in Go under pkg/observ: cache lookup total (Counter; labels: hit/miss + cache type), upstream fetch total (Counter; labels: success/failure), and upstream fetch duration seconds (Histogram, exponential buckets).
    • Designed with low-cardinality labels and zero API/storage changes; integrates with existing Prometheus, Datadog, and Stackdriver exporters. Added unit tests for all three metric paths
    • Go
    • Prometheus
  • PR - #3288

    Summary:

    • Identified a runtime panic in the schema parser where comment-based enum declarations assumed a non-empty type slice, causing crashes during spec generation when the type was uninitialized.

    Contributions:

    • Fixed a slice out-of-range panic by guarding access to sv.current.Type[0] and safely handling cases where the schema type was not yet initialized.
    • Preserved existing parsing behavior by passing an empty type to enum parsing logic when unavailable, ensuring backward compatibility.
    • Added a regression test covering the full Run() path with a swagger:model struct using comment-based enum declarations, reproducing the crash before the fix and validating correctness after.
    • Go

Projects

Skills

  • Go
  • Python
  • HTML
  • CSS
  • JavaScript
  • Tailwind
  • TypeScript
  • Node
  • MySQL
  • Git
  • GitHub GitHub
  • Next.js
  • React
  • Prometheus
Made by Abhishek