Senior Data Science Engineer
2 weeks ago
We are addressing exciting challenges for our customers, at the intersection of AI/ML and cutting-edge cloud infrastructure, with NLP being a core area of what we do and what we offer our customers.
Key Responsibilities">- ">
- Brainstorm and design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.">
- Use AI/ML to solve NLP tasks and hard challenges, primarily for internal projects and also for external projects.">
- Present effective, highly technical and complex solutions and architectures to audiences with limited or no experience in machine learning solutions.">
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- Advanced degree in Computer Science, Physics, Electrical Engineering, Statistics or Mathematics, preferably with specialization in Artificial intelligence, Machine Learning, Speech Recognition, Natural Language Processing, Operations Research, or a related field.">
- 7+ years of Industry experience in designing and implementing machine learning models at scale, with a track record of deploying them in large-scale production environments.">
- Experience with SotA attention models, Large Language Models (LLMs), Conversational AI, Virtual Assistants, Document Understanding, Spoken Language Understanding, Information Retrieval, Question/Answering or related fields.">
- Ability to work with minimal supervision, keeping a strong alignment with your technical peers, non-technical partners, and the overall company objective.">
- Fluent in building models with Python and state-of-the-art machine learning libraries (e.g. PyTorch, Tensorflow, MxNet).">
- Experience or willingness to learn and work in Agile and iterative development and DevOps processes.">
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- A deep experience and understanding in Statistics, Mathematical models, Multivariate and DL algorithms.">
- Experience in Machine Translation, Document Understanding, Reinforcement Learning with Human Feedback (RLHF), and Multimodal Deep Learning Models.">
- An impressive Google Scholar portfolio and a strong track record in starting or contributing to open-source ML platforms, tools, and projects.">
- Strong communication skills, with the ability to present effective, highly technical and complex solutions and architectures to audiences with limited or no experience in machine learning solutions.">
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