Applied AI/ML - Senior Associate
- Assist product leadership in defining the problem statements, execution roadmap
- Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, personalization, or recommendation systems.
- Collaborate with business, operations, and other technology colleagues to understand AI needs and devise possible solutions.
- Develop end-to-end ML/AutoML/AutoNLP pipelines and operationalize the end-to-end orchestration of the ML models to support the various use cases like Document Q&A, Search, Information Retrieval, classification, personalization, etc.
- Build both batch and real-time model prediction pipelines with existing application and front-end integrations.
- Collaborate to develop large-scale data modeling experiments, explain complex concepts to senior leaders and stakeholders.
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Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
- BS or MS or PhD in Computer Science or Data Science or Statistics or Mathematical sciences or Machine Learning. Strong background in Mathematics and Statistics.
- 5+ years' experience in applying data science, ML techniques to solve business problems and one of the programming languages like Python, Java, C/C++, etc.
- Experience with LLMs and Prompt Engineering techniques.
- 1+ year of experience working with Gen AI solutions / LLMs such as GPT, Claude, Llama etc.
- Solid background in NLP, Generative AI and hands-on experience and solid understanding of Machine Learning and Deep Learning methods and familiar with large language models
- Extensive experience with Machine Learning and Deep Learning toolkits (e.g.: Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
- Experience with Big Data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Experience with building and deploying ML models on AWS esp. using AWS tools like Sagemaker, EC2, Glue, etc.
- Have good understanding about the Active Learning, Agent/Multi Agent Learning, Learning from Supervision/Feedback, etc. Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
- Ability to work on tasks and projects through to completion with limited supervision. Passion for detail and follow through. Excellent communication skills and team player
- Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journals
- Experience with A/B experimentation and data/metric-driven product development
- Ability to develop and debug production-quality code and familiarity with continuous integration models and unit test development