Sharath Pai

Experience

From market segmentation and bioinformatics research to shipping LLM systems in production.

Resume

Education, experience, projects and skills on one page.

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  1. Sep 2025 – Present

    1 yr 2 mos

    Pune, India

    Jr. AI/ML Developer

    Eightinity Technologies

    • Applied DSPy for zero-shot prompt optimization across SLMs and LLMs, improving response consistency and robustness in production use cases.
    • Implemented LLM observability using Langfuse, monitoring latency, cost, and response quality to drive iterative optimization.
    • Engineered and maintained production-grade FastAPI services for serving AI pipelines, ensuring scalable inference.
    • Fine-tuned gemini-2.5-flash-lite on Vertex AI over 100+ epochs, generating optimized checkpoints for downstream inference tasks.
    • Deployed containerized AI services on Fly.io with persistent storage, autoscaling, and HTTPS, enabling stable production deployments.

  2. Oct 2024 – Jul 2025

    10 mos

    Nagpur, India

    Software Engineer, LLMs

    Salk AI

    • Benchmarked performance of LLMs, VLMs, STTMs with prompt engineering approaches like one-shot, few-shots, CoT.
    • Developed Proof of Concepts (POCs) involving LLMs, OpenCV and NLP based practices.
    • Traced the model API calls on Langfuse by integrating LLMs with LiteLLM and implementing fallback strategies.
    • Hosted open source models using vLLM with on NVIDIA A100 GPU and tested their performance with their endpoints.
    • Integrated AI into development environment by creating their RESTful backend APIs and user-friendly frontend interface.

  3. Jun 2024 – Jul 2024

    2 mos

    Avignon, France

    AI/ML Research Intern

    Avignon Université

    • Conducted research in Bioinformatics to analyze the impact of UV rays on living organisms using ML algorithms.
    • Developed datasets by extracting data from sources like NCBI and Springer.
    • Tuned ML models to predict UV ray impact, leveraging ANN architectures with BatchNormalization and Dropout layers.
    • Implemented predictive modeling techniques with Early Stopping and model-saving callbacks.
    • Integrated best-performing models into a Django-based web application for real-time UV ray impact prediction.

  4. Jan 2024 – Apr 2024

    4 mos

    Mumbai, India

    UI/UX Design Intern

    AI Chef Master

    • Performed user research regarding customer expectations and to identify the suitable elements for the webpage.
    • Planned the workflow and developed wireframes to ensure proper structuring of components.
    • Designed the complete portfolio website and the AI Chef website containing cuisines based on user preferences.
    • Worked with the Frontend Team to assist them with suitable color combinations and responsive layouts.
    • Created a prototype of all the designed pages to keep the applications organized useful for presentations.

  5. Nov 2023 – Jan 2024

    3 mos

    Remote

    Machine Learning Intern

    Feynn Labs

    • Developed a ML model on holiday packages using supervised learning algorithms to identify the customer purchase behaviour to be utilised for product creation for small/medium businesses.
    • Performed a case study on a restaurant dataset to identify the likeliness of customers with regards to age using K-Means++ Clustering and Principal Component Analysis.
    • Performed Market Segmentation Analysis for an Electric Vehicle startup to decide what customer space is suitable for developing its EVs throughout PAN India.