The successful candidate will work with world-class database gurus, software and machine learning engineers, research scientists, and fellow machine learning scientists. We are looking for someone who gets a kick out of staying on top of the latest machine learning and AI literature/tools/techniques and figuring out the best way to apply these for practical solutions. We encourage contribution to tools and knowledge sharing within the team, the company, and the industry.

Responsibilities

• Work with product management and leadership to translate business problems into data science problems

• Research, prototype, and build demonstrations of machine learning ideas for quick validation and feedback

• Design and build machine learning systems to hit accuracy and performance metric targets

• Productize machine learning systems in collaboration with engineering teams

• Design and conduct experiments to ensure optimal performance of machine learning systems

• Educate engineering and product teams about data science during collaboration

• Mentor and collaborate with other members of the data science team

• Share technical innovations with the team and across the company

• Create innovations and contribute to conferences and/or open-source tools

Qualifications
Must-Have

• Fluent in prototyping/building machine learning models and algorithms and wrangling large datasets

• BS/MS in a quantitative discipline with 2-3 years of relevant experience.

• Expertise in classical machine learning, deep learning, and large-language-models (LLMs)

• Proficient in using Python scientific stack (e.g. Numpy, Pandas, PyTorch, SciPy, Jupyter)

• Proficient in shell scripting, Unix/Linux command-line tools, working with cloud infrastructure (AWS)

• Great communication skills: ability to discuss with scientists, engineers, designers, and product managers

Nice to have

• Ph.D. with 1+ years of relevant experience

• Experience in shipping machine learning models into large-scale production systems

• Deep Experience in reinforcement learning, deep learning, causal inference, and information retrieval

• Experience in building machine learning models for e-commerce problems like search and recommendations

• Open-source machine learning code from one's paper, contributions to any projects, implementations of papers

• Publications in any of {cvpr, iccv, eccv, neurips, iclr, icml, acl, emnlp, recsys, kdd}

•