Research Scientist, Machine Learning (PhD) Responsibilities

• Proactively identify and drive changes as needed for your assigned codebase, product area and/or systems
• Build strong cross functional partnerships and code deliverables
• Suggest, collect and synthesize requirements and create effective feature roadmaps
• Perform specific responsibilities which vary by team

Minimum Qualifications

• Currently has, or is in the process of obtaining, a PhD degree or completing a postdoctoral assignment in the field of - Computer Science, Computer Engineering or relevant technical field. Degree must be completed prior to joining Meta
• Currently has, or is in the process of obtaining a Bachelors degree in Computer Science, Computer Engineering, r-relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Relevant experience using frameworks such as PyTorch, TensorFlow or equivalent
• Proven experience to translate insights into business recommendations
• Experience building and shipping high quality work and achieving high reliability
• Experience in systems software or algorithms
• Experience programming in a relevant language
• Experience identifying, designing and completing medium to large features independently, without guidance
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications

• Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)
• Research and/or hands-on experience in one or more of the following areas: Machine Learning, NLP, Recommendation Systems, Pattern Recognition, Data Mining, Computer Vision, Artificial Intelligence or other relevant fields
• Experience with programming languages such as Python, R, MATLAB
• Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as KDD, NeurIPS, ICML, WWW, ACL, ICLR, CVPR or similar
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward
• Interpersonal experience working and communicating cross functionally in a team environment
• Exposure to architectural patterns of large scale software applications