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Senior ML
4 months ago
Senior ML / Generative AI Developer
Remote
Our client is a global leader in Telecommunications, wireless and IoT solutions. This role is part of their advanced research and product development teams and is working on the cutting edge of AI-driven automation. With this group you will be designing and building customized and complex LLM’s to support of variety of IoT, product network and client support use cases across multiple verticals. Innovation drives this practice group and they are on the leading edge of Generative AI and Deep Learning.
Duration: 12 Months+ Required Skills & Experience
The ideal candidate should have at least 5 years of professional experience as a Machine Learning Developer and at least 1-2 years of expertise in implementing Gen AI technologies to derive meaningful insights from large datasets.
Strong proficiency in Python and relevant frameworks and libraries such as TensorFlow, PyTorch, Pandas, Numpy, and scikit-learn.
Proficiency in machine learning, deep learning, and data mining techniques.
Strong of experience in Generative AI/LLMs and should be adept at delivering and productionizing.
At least 3 years of experience in software engineering, building REST APIs/GraphQL and/or interfaces using frameworks like FastAPI, Flask, or Django.
The candidate should demonstrate skills and experience with the latest LLM tools and techniques such as LangChain, Promptflow, vector DB, prompt engineering, etc.
Should possess strong expertise in GenAI pipelines, various language models (LLM) like GPT-4, BERT, or LLAMA, and retrieval-augmented generation (RAG) systems.
Should stay updated with the latest advancements in generative AI, Large Language Models (LLMs), and prompt engineering and bring innovative ideas to the team.
What You Will Be Doing
Work closely with cross-functional teams, including data scientists, product managers, and business analysts to understand their requirements and implement effective GenAI solutions.
Collaborate with engineering and product teams to integrate prompts into applications, identify technical challenges, and implement innovative solutions.
Write efficient, reusable, and modular Python code for the implementation of GenAI algorithms and models.
Deploy LLM projects to production and define success-measuring criteria/KPIs.
Lead the design and development of artificial intelligence solutions, specifically leveraging Python for GenAI applications.
Implement testing strategies to ensure the reliability and accuracy of GenAI models, troubleshoot issues, and optimize performance.
Create and maintain comprehensive documentation for GenAI solutions, including design specifications, coding standards, and deployment.
