Lead the efforts building distributed training and inference support into Pytorch, Tensorflow, Jax using XLA and the Neuron compiler and runtime stacks. This role will help tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and the TRn1 , Inf1 servers.

• Improved modelling performance from close to 0 to around 96% hit rate according to business to optimize their processes.

• Designed and implemented modelling framework from ground up and brought it to production.

• Implemented modular framework for feature calculation and aggregation to consider different time horizons, statistics, and selection criteria. Framework could be understand by non-experts. Boosted number of features from 38 to more than 6500.

• Implemented modelling pipeline to predict and measure drug efficiency.

• Implemented modular framework for table transformation ML pipelines to enable version tracking, logging, and application for inference. Tuned performance of pipeline. (PySpark, Databricks, MLFlow)

I managed up to 8 direct reports, including change management, teaching, and coaching. I handled human resources / people management issues, such as salary assessment, leave, and performance review.

• Drove product delivery, communicating 1-on-1 with stakeholders, connecting right people to each project, strategizing on plan and execution, and deescalating and ramping down projects to achieve business and customer objectives.

• Defined a new department structure, explaining and implementing changes gradually to gain buy-in and increased organizational efficiency to reduce time from customer engagement to product delivery.

I collaborated with customers and colleagues to accelerate customer and benchmark models based on implementation, analysis, and optimization skills. I documented research and approaches for marketing.

• Boosted sales activity by delivering improved performance in alignment with main competitor, including marketing material used in almost every customer interaction: deep learning performance benchmark (MLPerf) submission with 3.2x speed-up in ResNet-50 and 2x speed-up with packing in Natural Language Processing.

• Tuned 8 customer models on IPU (GNNs, image processing, prob. models, RL [MiniGo]), using software development, problem solving, and communication skills, which enabled public applications for marketing and sales team interaction.

• Wrote and presented 11 scientific papers, documentation, performance guides, scaling guide, and blogs, drawing on research and writing skills to create marketing and educational material that promoted company hardware as tool for accelerating research and educating customers and colleagues on how to optimize applications.

• Organized 1-2 team meetings per week to educate and encourage collaboration for better motivation and deliverables.

• Recognized as top performer for supporting business mission achievement, including driving profitable sales growth, serving as role model to others, and building internal and external partnerships across functions and at all levels, 2021.

I managed up to 3 direct reports and 4 big data analytics / predictive algorithms projects to support driver display interaction.

• Wrote 2 white papers and 10 patent proposals (5 filings), documenting current and future innovation to protect knowledge and ideas and future revenue.

• Analyzed large-scale customer data, verifying data for sales use and creating POC for data usability, including existing part specification verification for quality team.

• Improved the customer car experience by fixing mathematical errors with my analytical skills and implementing evaluation frameworks and new predictive algorithms.