Jobs

    Machine Learning Engineer - Bangalore, India - Pyxidia Techlab LLP

    Pyxidia Techlab LLP
    Pyxidia Techlab LLP Bangalore, India

    Found in: Talent IN 2A C2 - 6 days ago

    Default job background
    permanent Engineering / Architecture
    Description

    Job Description :
    What will you do?

    • Implement technology solutions using Large Language Models (LLMs) like GPT
    • Fine tune LLMs with proprietary data
    • Use LLMs in conjunction with other domain specific models like Vision, NLP, Speech recognition, Image generation
    • Setup integrations with hosted LLMs using various cloud providers (AWS+HuggingFace, Azure+OpenAI, Google+Bard)
    • Setup and integrate hosted LLM models.
    • Enhance the hosted LLM models with proprietary data.
    • Write APIs using Python/Go to enhance and Integrate with existing API infrastructure.
    • Design Prompts that provide appropriate responses.
    • Use various prompt engineering methods (introspection, chainofthought, instruction prompting).
    • Work with data teams to collect and organize the data needed for the task at hand.
    • Ensure that best practices are followed in solving AI problems including thorough problem analysis, prior research understanding, persistent experimentation and documentation, rapid prototyping and extensive testing.
    • Help in filing for patents and publishing research papers at AI conferences.
    • Extensively document learnings from experiments and share with ML engineering team
    • Use Copilot/CodeWhisperer in developing code and create "cookbook" for good code generation.
    What you need to have?

    • Handson industry experience of 1 to 2 years working on machine learning and deep learning or related fields.
    • Sound understanding of Deep Learning in at least two AI problem domains, preferably, Computer Vision, NLP/NLG using LLM, Time Series Forecasting.
    • Having a strong mathematical background in linear algebra, probability, and calculus.
    • Familiar with machine learning frameworks such as PyTorch or TensorFlow, Keras.
    • Proficient in Python based programming
    • Understanding of modeling a problem into a Deep Learning framework.
    • Exposure in building, measuring and iterating on neural network architectures that effectively solved the problem
    • Experience working in a productbased startup environment
    • Understanding of pipelines to monitor, extract, index, build and tune ML and NLP models
    • Experience working in collaborative software development environments including the use of git, peer code review and independent authorship of well tested, maintainable and documented code.
    • Data Management
    • Defining validation strategies
    • Defining the preprocessing or feature engineering to be done on a given dataset
    • Defining data augmentation pipelines
    • Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
    • Working proficiency with SQL and relational databases, data warehouse.
    • Experience with GPU/CUDA for computational efficiency.
    • Experience with ML Ops frameworks like Sagemaker/AWS, MLFlow or similar
    • Familiar with distributed computational frameworks (YARN, Spark, Hadoop)
    )
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