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• EAD (OPT/CPT/GC/H4)

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• Corp-Corp

• W2-Permanent

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• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 14th Aug 2024

Ø In-depth knowledge of Deep Learning and Neural Network architectures, with multiple years of hands-on experience.
Ø Proven track record in developing prototypes and deploying/productionalizing solutions leveraging big data.
Ø Expertise in Autoencoders, Neural Networks, RNN, CNN, GNN, LSTMs, and other advanced neural network models.
Ø Exceptional Python coding skills, including development, debugging, and production-quality coding.
Ø Extensive experience in handling and processing large volumes of document data, including financial, legal, regulatory, and policy data.
Ø Strong understanding of NLP classification tasks and their application in various projects.
Ø Proficient in parallel experimentation, GPU utilization, distributed computing, and Spark ML.
Ø Ability to accurately scope and estimate GPU usage for model training and deployment.
Ø Hands-on experience with LLMs and Generative AI algorithms, including development and fine-tuning.
Ø Proficient in using GitHub for version control, and experienced in deployment processes.
Ø Skilled in Kubernetes, AWS, and designing robust solution architectures.
Ø Experience with MLOps or AIOps practices to streamline machine learning workflows.
Ø Publication record in key AI/ML conferences or journals, demonstrating thought leadership in the field.
Ø Ability to effectively showcase and communicate work to various stakeholders.
Ø Strong Agile mentality, with experience working in Agile development environments and familiarity with Agile methodologies such as Scrum or Kanban.
Ø Excellent problem-solving skills and the ability to think critically and creatively to develop innovative solutions.
Ø Strong collaboration and teamwork skills, with the ability to work effectively in cross-functional teams.
Ø Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders.
Ø Strong project management skills, with the ability to manage multiple projects and priorities simultaneously.
Ø Commitment to continuous learning and staying up-to-date with the latest advancements in AI, Machine Learning, and related fields.
Ø Experience in mentoring and guiding junior team members, fostering a collaborative and growth-oriented team culture.
Ø Advanced technical skills in graph or contextual attention mechanisms, hierarchical modeling, and agent-based modeling.
Ø Expertise in Named Entity Recognition (NER) and other advanced NLP techniques.
Ø Excellent command of linear algebra and its applications in machine learning and deep learning.
Ø Familiarity with hierarchical modeling techniques for complex data structures.
Ø Experience with graph-based algorithms and their applications in machine learning.
Ø Proficiency in contextual attention mechanisms to enhance model performance.
Ø Expertise in prompt engineering for optimizing AI model interactions.
Ø Advanced knowledge of Generative AI use case architectures and algorithms, including advanced Retrieval-Augmented Generation (RAG), Generative Adversarial Networks (GANs), Contrastive Learning, Transfer Learning, and K-shot Learning.
Ø Proficiency in working with large language models and transformers.
Ø Strong understanding of graph theory and its applications in neural networks.