Location
Bangalore North | India
Job description
About Loyalytics:
Loyalytics is a fast-growing Analytics consulting and product organization based out of Bangalore. We work with large retail clients across the globe helping them monetize their data assets through our consulting assignments and product accelerators. We are a young dynamic team of 100+ analytics practitioners working on some of the most cutting-edge tools and technologies.
Who we are:
● Technical team: A team full of data scientists, data engineers and business analysts who work with 1M+ data points every day.
● Market Size: Massive multi-billion $ global market opportunity.
● Leadership: Combined experience of 40+ years of experience in the industry.
● Customers: Word-of-mouth and referral driven marketing to acquire customers like big retail brands in GCC regions like Lulu, GMG, among others (Strong product-market fit).
● What makes us stand apart: 8 years old bootstrapped and 100+ people company that is still hiring.
About the job
This role is for an experienced Artificial Intelligence Engineer on the Marketing Data Science team at HP.This individual will be responsible for helping the team to shape its AI strategy, specifically through the creation of AI models, such as Large Language models (LLMs) and Natural Language Processing (NLP), for Marketing. Marketers are tasked with combing through tons of research and data to find appropriate insights; there is oftentimes too much information and too little time. This individual will provide Marketers with curated AI tools that help them to have the right information at the right time to make the best decisions. This is a fantastic opportunity to be part of cutting-edge AI work that enables Marketing to drive innovation and business growth.
Job Locations: Bangalore/Gurgaon/Delhi, On-site or Hybrid
Responsibilities
- Design the architecture and environment to enable AI models to run
- Assess which environments are most appropriate, whether current compute is
- sufficient, whether we should choose an existing model or pretrain our own
- Lead AI model construction to both evolve existing capabilities and create new ones
- Apply AI to Marketing use cases to improve customer intelligence and data analytics
- Teach Data Scientists how to use the created LLMs to analyze structured and unstructured data
- Build AI applications and interfaces at scale for the bigger Marketing organization to use
- Advise the team on best practices for AI models (i.e. parameters, data structure, etc.)
- Evaluate LLM performance using different applications and file formats to identify the best
solution
- Debug and identify causality for issues in the AI results
- Research new AI models and trends to understand how we can maximize the usage of our
existing models and/or whether we should adopt new models
Requirements
- Strong knowledge of ML and Deep Learning in the context of LLMs, NLPs and chatbots
- Experience working with AI models using real-life (“industry”) data
- Expert Python skills (PyTorch/TensorFlow, Pandas, NumPy, Matplotlib, creating functions)
- Mastery in tool usage (AWS, Jupyter notebook, Streamlit or similar UIs)
- Expertise in building and fine-tuning LLMs; experience with PEFT methods and alignment with
human feedback (RLHF)
- Expertise in Prompt Engineering using various AI models
- Understanding of the differences and advantages of Llama, Falcon, and other open source LLMs
- Experience utilizing structured and unstructured data in LLMs (CSV, Json, TXT, PDF)
- Mastery in database engineering (Relational and Vector databases/Embeddings)
- Proficiency in AI frameworks (Langchain, Agents, Transformer Architecture etc.)
- Experience utilizing both Generative and Discriminative AI models for data querying and
representation
- In-depth knowledge of big data platforms, statistical software and machine learning algorithms
packages
Benefits
- Be a part of the dynamic and fun team, making an impact in the retail tech industry with clients like Lulu, Aster, GMG etc.
- Flexible Work Hours.
- Wellness & Family Benefits.
- Access to various learning platforms.
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