Dhruv Diddi

Co-Founder

San Francisco, California, United States9 yrs 3 mos experience
Most Likely To SwitchAI Enabled

Key Highlights

  • Founder of Solo Tech focusing on Physical AI.
  • Led machine learning initiatives at Turo and Google.
  • Expertise in computer vision and real-time systems.
Stackforce AI infers this person is a Machine Learning and Computer Vision expert in the SaaS industry.

Contact

Skills

Core Skills

Applied Machine LearningMlopsMachine LearningSoftware EngineeringComputer VisionResearch EngineeringSystem Engineering

Other Skills

Physical AI SkillsRealtime performanceHardware optimized modelsAIoTPerformance trackingInference improvementsAutomated trainingTesting processesPythonKafkaControl systemsObject recognitionScene understanding algorithmsYOLOXDeep Sort

About

Engineer based in the San Francisco Bay Area with experience in Applied Machine Learning, MLOps, Computer Vision, and Full Stack Development! Web Site: https://www.getsolo.tech/

Experience

9 yrs 3 mos
Total Experience
1 yr
Average Tenure
1 yr 5 mos
Current Experience

Solo tech

Founder

Dec 2024Present · 1 yr 5 mos · San Francisco Bay Area

  • ✔︎ Who benefits from Solo Tech?
  • ∙ Projects utilizing Physical AI Skills
  • ∙ Enterprises post training models for realtime performance
  • ∙ Devs deploying hardware optimized models on robots and AIoT
  • Train Robot Skills
  • #OwnYourAI
  • www.getsolo.tech
Physical AI SkillsRealtime performanceHardware optimized modelsAIoTApplied Machine LearningMLOps

Turo

Senior Software Engineer (Machine Learning)

Feb 2022Jan 2024 · 1 yr 11 mos · San Francisco Bay Area

  • Introduced performance tracking and inference improvements (3.5-4X p99) for multiple domains
  • Updated automated training, testing, and deployment processes for Turo Search (1.4k RPM)
  • Designed and implemented Python inference endpoint deployment for Risk and Safety
  • Led demo development of LLM-based solutions for Customer Support and Company IP Assets
  • Supported development of Kafka-based messaging for cross-domain Feature Store
Performance trackingInference improvementsAutomated trainingTesting processesPythonKafka+2

Flovision solutions

ML Lead (Computer Vision)

Dec 2020Jan 2022 · 1 yr 1 mo · Mountain View, California, United States

  • Developed control systems and object recognition pipeline for MVP with real-time metrics
  • Integrated scene understanding algorithms for detection (YOLOX) and tracking (Deep Sort)
  • Managed and led team tasks from no product to 3 paid customers with 10+ locations
Control systemsObject recognitionScene understanding algorithmsYOLOXDeep SortComputer Vision+1

Badge biometrics

Founding Engineer (Computer Vision)

Jun 2019Sep 2020 · 1 yr 3 mos · Fremont, California, United States · On-site

  • Implemented CV/NLP algorithms to guardrail biometrics (Face, Fingerprint, Voice) extraction
  • Architected ML pipeline with quantization strategies using FaceNet-like embedding
CV/NLP algorithmsML pipelineQuantization strategiesFaceNetComputer VisionMachine Learning

Google

2 roles

Computer Vision Software Engineer

Sep 2017May 2019 · 1 yr 8 mos · San Francisco Bay Area

  • Implemented optical flow and segmentation to get accurate human body pose and fit
  • Prototyped meshing algorithms for AR clothing trial product using CGAL (CPP) graphics
Optical flowSegmentationCGALMeshing algorithmsComputer VisionSoftware Engineering

Software Engineering Intern

May 2017Aug 2017 · 3 mos · San Francisco Bay Area

  • Developed CV/ML algorithms for image segmentation and dense motion estimation for ATAP
  • Designed backend pipeline and database system for logging and analytics
  • Created dataset to train and test RNN models for image processing pipeline
CV/ML algorithmsImage segmentationDense motion estimationBackend pipelineDatabase systemComputer Vision+1

Distributed autonomous systems lab

Research Engineer

Sep 2016May 2017 · 8 mos · Urbana-Champaign, Illinois Area

  • Under the guidance of Prof. Girish Chowdhary, we work on algorithms and control system implementations for distributed and networked autonomous systems like drones.
  • We create solutions to real life problems in agriculture and aeronautics.
  • Develop reinforcement learning (Q Learning) solutions to drone situational problems.
AlgorithmsControl systemsReinforcement learningResearch EngineeringMachine Learning

Youtube

Software Engineering Intern

May 2016Aug 2016 · 3 mos · Los Angeles, California

  • Introduced backend infrastructure of support feed rendering in Subscriptions on mobile app.
  • Created a feature for Subscriptions recommended feed which has tens of millions of daily active users, completely revamping the way users see and use YouTube.
Backend infrastructureMobile app developmentSoftware Engineering

Etsy

Software Engineering Intern

Jun 2015Aug 2015 · 2 mos · San Francisco Bay Area

  • Developed Translation Memory for listings content on EtsyWeb leading to $600K savings for Etsy.
  • Developed One-Click Translation conversation UX which produced a 1.44% conversion rate increase.
  • Created a ML model for spam detection and conversation translation for all messages on Etsy.
  • Designed pipeline for Auto deployinator for translation dump.
Translation MemoryML modelPipeline designSoftware Engineering

Google

CodeU Fellow

Jan 2015Jul 2015 · 6 mos · San Francisco Bay Area

  • CodeU is a program for students to work on Android and technical exercises through pairing with Google mentors.
  • Won Engineer's Choice Award for IVO, a content-to-geolocation locking app at the end of the program.

National center for supercomputing applications

Lead Engineering Intern

Sep 2014May 2015 · 8 mos · Champaign, IL

  • Developed a workflow for live auto captioning and creation of standard caption files for use in video editing, utilizing and enhancing Speech-To-Text HPC/cloud services and Sphinx NLP Library to create transcripts for people in DRES..

Cazoodle

System Engineer

Nov 2013Sep 2014 · 10 mos · Research Park

  • Cazoodle provides software and internet services for Web search, integration, and mining, with a central objective to "deepen" search on the Web to access the vast amount of data beyond the reach of current search engines. As a System Engineer, I was responsible for maintaining the overall enterprise IT infrastructure. While working at Cazoodle, I learned to manage and configure Hadoop server machines. It was also interesting to work on Linux as well as Windows to analyze DNS and LDAP network configurations.
Speech-To-TextNLP LibrarySoftware Engineering

University of illinois at urbana-champaign

Web Developer

Oct 2013Dec 2013 · 2 mos · School of Business

  • As a Web Developer for the College of Business, I was selected to adapt the EMBA program website into a mobile responsive website through CSS by making dynamically responsive objects. Its was a great experience working on Drupal CMS and Wordpress too, while setting up the websites. I've also got to explore implemented HTML5 themes on the subsistence education portal of UIUC Business to enhance usability and legibility of the content on the page by designing content and article tabs for website.

Ikenberry commons executive board

Programming Chair

Oct 2013Dec 2013 · 2 mos · University of Illinois at Urbana-Champaign

Acm gamebuilders

Student Mentor

Sep 2013May 2014 · 8 mos · University of Illinois at Urbana-Champaign

  • Promoted game building through code demonstrations and implementations.
  • Engaged mentees on working on pre build Game Engine environments like Unity and Box2D.
  • Designed coding modules to present good programming practices and gave lessons on game development.
HadoopLinuxWindowsDNSLDAPSystem Engineering

Education

University of Illinois Urbana-Champaign

Bachelor of Science - BS [INC] — Computer Engineering

Jan 2013Jan 2017

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