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Estimated Pay $63 per hour
Hours Full-time, Part-time
Location Raritan, New Jersey 08869
Raritan, New Jersey

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We estimate that this job pays $62.53 per hour based on our data.

$34.39

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$100.92


About this job

Location – Raritan, NJ 4 days Onsite FTE/C2C Job Description · Must have 12+ years of experience working in Data science, Machine learning and especially NLP technologies. · Exposure to various LLM technologies and solid understanding of Transformer Encoder Networks. · Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence. · Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, including but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures. · Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment. · Very good understanding of Prompt engineering techniques in developing Instruction based LLMs. · Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization. · Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs. · Passionate to learn and stay updated with the latest advancements in generative AI and LLM. · Nice to have -contributions to the research community through publications, presentations, and participation in relevant conferences or workshops. · Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for training and evaluation of generative models. · Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed. · Exposure to developing Guardrails for LLMs both with open source and cloud native models. · Collaborate with software engineers to deploy and optimize generative models in production environments, considering factors such as scalability, efficiency, and real-time performance. · Nice to have- provide guidance to junior data scientists, sharing expertise and knowledge in generative AI and LLM, and contribute to the overall growth and success of the data science team.