Naila Farooqui
Backend EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Engineering Director (GenAI)
Interested in building massively intelligent systems that are designed to work in harmony with human goals and values. Accomplished computer science researcher and software engineer, specializing in object-oriented approaches to systems development, with a unique blend of compilers, architecture, and machine learning expertise. My Ph.D. dissertation work was on the design and development of software execution environments for heterogeneous systems, specifically targeting heterogeneous GPU platforms. Research Interests: Compilers and Programming Languages (Dynamic Instrumentation Techniques), Computer Architecture, Computer Systems, Machine Learning & Large Language Models
Stanford University
Ph.D. Minor, Entrepreneurship
January 1, 2014 – January 1, 2015
Georgia Institute of Technology
Doctorate, Computer Science
January 1, 2010 – January 1, 2015
Georgia Institute of Technology
Bachelor of Science, Computer Science
January 1, 2000 – January 1, 2003
RelationalAI
Director, Engineering (Generative AI)
February 1, 2025 – Present
TensorWave
Senior Staff ML Systems Engineer (ScalarLM)
February 1, 2025 – Present
Lamini
Machine Learning Systems Builder
June 1, 2024 – December 1, 2024
On-site
Apple
Senior ML Systems Engineer, SPG
March 1, 2023 – June 1, 2024
FIRST Robotics
Head Coach - FRC Team 9006 (Crescent Wing Robotics)
August 1, 2022 – Present
San Jose, California, United States
Apple
Senior Deep Learning Compiler Engineer
February 1, 2020 – March 1, 2023
NVIDIA
Senior Deep Learning Compute Architect
May 1, 2017 – January 1, 2020
Intel Labs
Research Scientist
December 1, 2015 – May 1, 2017
Santa Clara
Intel Labs
Research Intern
September 1, 2014 – September 1, 2015
Santa Clara, CA
Hewlett-Packard Laboratories
Research Associate
February 1, 2014 – September 1, 2014
Microsoft Research Silicon Valley
Graduate Research Intern
April 1, 2013 – August 1, 2013
Mountain View, California
Georgia Institute of Technology
Graduate Research Assistant
August 1, 2010 – December 1, 2015
Infinovate
Staff Software Engineer
May 1, 2010 – December 1, 2010
Self-Employed
Independent Software Consultant
February 1, 2009 – March 1, 2010
PICA Group
Senior Software Engineer
July 1, 2007 – February 1, 2009
Dell
Software Engineer
June 1, 2003 – July 1, 2007
CUTLASS
May 1, 2017 – Present
CUDA Templates for Linear Algebra Subroutines
GPU Lynx
September 1, 2012 – May 1, 2015
Lynx: A Dynamic Instrumentation System for GPGPU Computing
Cultural Fit Analysis
The candidate demonstrates a strong background in research and development within large corporations and startups, indicating adaptability to different organizational cultures. Their involvement in open-source projects (ScalarLM, CUTLASS) and coaching (FIRST Robotics) suggests a collaborative and mentorship-oriented mindset. However, the target role is 'Backend Engineer' while the recent experience is heavily focused on 'ML Systems Engineer' and 'Generative AI'. While there's overlap, the specific backend engineering aspects (e.g., API design, database interactions, distributed systems beyond ML infrastructure) are not explicitly detailed, which might indicate a slight misalignment if the role is not purely ML infrastructure focused. The candidate's experience is highly specialized in ML/AI systems, which could be a strong fit for an AI-centric backend role but less so for a general backend position.
Soft Skills & Operational Fit
The candidate's resume highlights leadership roles (Director, Engineering; Head Coach) and collaborative project development (co-developed ScalarLM, CUTLASS 2.0), suggesting strong soft skills in leadership, teamwork, and project ownership. The detailed descriptions of complex system builds indicate a methodical and problem-solving approach. However, without psychometric test results, a definitive assessment of work attitude, stress handling, and team collaboration cannot be made.