- Research and Analysis : Conduct research and analysis to understand customer requirements and challenges in implementing Large Language Models (LLMs) for various applications.
- Model Development : Develop and implement machine learning models, including LLMs, tailored to meet customer needs and industryspecific use cases.
- Optimization and Fine-Tuning : Optimize and finetune machine learning models for improved performance, accuracy, and efficiency, leveraging techniques such as hyperparameter tuning, transfer learning, and reinforcement learning.
- Deployment and Integration : Deploy machine learning models into production environments, ensuring seamless integration with existing systems and infrastructure.
- Testing and Validation : Conduct rigorous testing and validation of machine learning models to ensure reliability, scalability, and robustness in realworld scenarios.
- Performance Monitoring : Monitor and analyze the performance of deployed models, identifying opportunities for optimization and improvement.
- Collaboration and Communication : Collaborate with crossfunctional teams, including data scientists, software engineers, and domain experts, to gather requirements, iterate on solutions, and communicate progress and findings effectively.
- Documentation and Reporting : Document model development processes, methodologies, and findings, and prepare comprehensive reports and presentations for internal stakeholders and customers.
- Continuous Learning and Innovation : Stay updated on the latest advancements in machine learning and natural language processing (NLP), and explore innovative approaches and techniques to enhance model performance and capabilities.
- Bachelor's/Master's/Ph.
- At least 5+ years of relevant experience as an AI Developer
- Should have deep knowledge in machine learning techniques and algorithms, with a focus on natural language processing (NLP) and large language models (LLMs).
- Experience with language modeling evaluation, prompt tuning and engineering, instruction tuning, and/or RLHF
- Prior experience with training and finetuning of foundation models such as GPT3, LLaMA2, AlphaFold, and DALL-E
- Knowledge of deep learning architectures, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformer models.
- Experience in Information Extraction, Question Answering, Conversational Agents (Chatbots), Data Visualization and/or texttoimage models
- Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
- Strong communication and collaboration skills, with the ability to work effectively in crossfunctional teams.
- Open Source Contributions : Candidates who have contributed to opensource projects related to machine learning, natural language processing, or large language models will be given preference.
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Description
Job Description :
The Data Scientist role at Maxim is a high-impact, self-directed role and covers a broad scope of work across RAG, fine-tuning LLMs, synthetic data generation and more.
This role involves keeping up-to-date with the latest advancements in LLM technologies and research, and utilizing these advancements to enable AI developers in crafting more magical experiences.
Key Responsibilities :
Desired Skills and experience :