GenAI Researcher - Remote​/Telecommute

Job Description:

• The GenAI Researcher will focus on developing and optimizing domain-specific Large Language Models (LLMs) and Small Language Models (SLMs) to solve complex, domain-driven challenges.
• This role involves advanced research and hands-on development across supervised fine-tuning, reinforcement learning from human feedback (RLHF), pre-training, post-training, evaluation, and multimodal model development.
• The researcher will collaborate closely with cross-functional teams to translate research into production-ready solutions.

• Conduct cutting-edge research in natural language processing and develop advanced SLMs and LLMs for domain-specific applications.
• Design, implement, and optimize language models to efficiently solve domain-specific problems.
• Analyze, clean, and preprocess large-scale datasets to ensure high-quality training inputs for language models.
• Design, evaluate, and benchmark model performance using appropriate metrics and continuously iterate on improvements.
• Develop and implement methods to enhance model capabilities, reliability, robustness, and safety.
• Collaborate with domain experts, data engineers, and software engineers to integrate models into production systems.
• Publish research findings in top-tier conferences and journals and communicate results to technical and non-technical stakeholders.
• Stay current with advancements in NLP, machine learning, and artificial intelligence and apply relevant techniques to ongoing work.

• Strong expertise in supervised fine-tuning and reinforcement learning from human feedback (RLHF).
• Solid understanding of fine-tuning strategies including full fine-tuning and parameter-efficient fine-tuning techniques such as LoRA and QLoRA.
• Proven experience working with generative AI frameworks such as Lang Chain, Lang Graph, Llama Index, and Lang Smith.
• Strong machine learning, reinforcement learning, and research-oriented software engineering skills.
• Hands-on experience improving or extending pretrained SLMs and LLMs.

• Minimum of 2 years of experience developing and optimizing SLMs and LLMs, including foundation model training and fine-tuning.
• At least 5 years of research experience in one or more of the following areas: NLP, speech processing, computer vision, multimodal systems, machine learning, or deep learning.
• Industry or research experience with large-scale data processing, distributed computing, or cloud-based AI systems is preferred.
• Experience deploying AI models on cloud platforms such as AWS, Azure, or Google Cloud is a plus.

• Proficiency in Python programming.
• Hands-on experience with ML and NLP frameworks including PyTorch, Tensor Flow, and Hugging Face.
• Strong understanding of model evaluation, benchmarking, and performance optimization.
• Ability to translate domain knowledge into effective AI model solutions.
• Familiarity with responsible AI practices and regulatory compliance is a plus.
• Excellent written and verbal communication skills with the ability to explain complex technical concepts clearly.
• Strong collaboration skills and ability to work effectively in cross-functional teams.

• Ph.D. in Computer Science, Computational Linguistics, Data Science, Artificial Intelligence, or a related field with a focus on NLP or machine learning.
• Bachelor s or Master s degree in Computer Science, Computer Engineering, or a related technical field is also acceptable with strong relevant experience.