Senior Applied Scientist (AI)

TL;DR

Senior Applied Scientist (AI): Researching, designing, developing, and evaluating generative AI solutions to address real-world challenges with an accent on model selection, training, tuning, right-sizing, distillation, and hardware optimization. Focus on Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques.

Company

hirify.global Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform.

What you will do

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges.
• Interact with customers directly to understand their business problems and guide them on adoption patterns and paths to production.
• Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization.
• Provide customer and market feedback to product and engineering teams to help define product direction.

Requirements

• PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience, or Master’s degree plus 10 years of relevant work experience.
• 5+ years of hands on experience with Python to build, train, and evaluate models.
• 5+ years of experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
• 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques.
• Scientific publication track record at top-tier AI/ML/NLP conferences or journals.

Nice to have

• Demonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customization.
• Experience with model optimization techniques (quantization, distillation, compression, inference optimization etc.).
• Experience with open-source frameworks for model customization like trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/ or similar tools.
• Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts.
• Demonstrated ability to identify and frame technical problems from broad product-level and business-level problem areas.

Culture & Benefits

• AWS values diverse experiences and encourages candidates to apply even if they do not meet all of the qualifications and skills listed in the job description.
• Employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
• Endless knowledge-sharing, mentorship and other career-advancing resources are here to help you develop into a better-rounded professional.
• We value work-life harmony and strive for flexibility as part of our working culture.