About the role
Experience with latest advancements in embedding models is preferred. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research). OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research). OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research). These
requirements include but are not limited to the following specialized security screenings: Bachelor's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics predictive analytics, research). OR Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research). OR Doctorate in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ year(s) related experience (e.g., statistics, predictive analytics, research). OR equivalent experience. 3+ years of Python coding skill. Experience in post training of foundation models. Advance the science: Design and run experiments, define and validate metrics, and develop ML pipelines and models in areas like post training foundation models, encoder-decoder models, cross-encoder models. You will be working with large scale data and derive insights out of it while championing Privacy and Compliance. As a senior member in
the team, you are expected to work with different parts of the stack as well as different team members to drive optimum designs and architectures. Drive product innovation: Partner with Engineering, PM, and Design to translate product vision and industry trends into scalable, reliable, and agile architecture. Champion customer impact: Engage with customers and internal teams to deeply understand pain points and drive improvements that matter. Lead and mentor: Provide technical leadership to team , and scale your learnings across the broader product group. Define success: Influence thorough model evaluation processes and generate insights from model experimentation. Establish and evolve success metrics that reflect platform and product growth. Stay ahead: Keep up with the latest research and foster a thriving applied science culture. Publishing is encouraged, though not required.
