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Machine Learning Engineer - Python / LLM

Machine Learning Engineer - Python / LLM

Pyxidia Techlab LLPChhattisgarh
30+ days ago
Job 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, chain-of-thought, 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?

  • Hands-on 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 product-based 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 pre-processing 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)
  • (ref : hirist.tech)

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