# Adnaan Sachidanandan > AI Engineer | Berkeley and Cambridge Grad Location: San Francisco Bay Area, United States Profile: https://flows.cv/adnaan I am an Applied AI engineer at Serval. For more information see https://adnaan.co ## Work Experience ### Applied AI Engineer @ Serval Jan 2026 – Present ### Software Engineer - AGI @ Amazon Jan 2024 – Jan 2026 Inference for multimodal models, specifically Nova Sonic and Nova 2 Sonic ### Founding Engineer @ Vocode Jan 2023 – Jan 2024 Building platform for conversational AI for phone calls, orchestrating LLMs, transcription models, and voice synthesis models. Joined as one of the first technical hires, focusing on core technical challenges in model performance, conversation latency, system scalability, and reliability. Notably focusing on fine-tuning models (customer agents, voicemail detection), ML lifecycle pipelines (data collection/cleaning, training infra, model evaluation suites), observability (Sentry integration, system logging), and core features (integration of model providers like Anthropic, model fallback mechanisms, interruption handling, etc.). Led internal and customer projects, designed our engineering on-call process, helped with candidate interviews and hiring, and contributed to open-source repo (https://github.com/vocodedev/vocode-core). ### Graduate Researcher @ Department of Engineering at the University of Cambridge Jan 2023 – Jan 2023 Researched 3D topological reconstruction techniques using foundation and large-language models. This research was done prior to the release of modern multimodal LLMs like GPT4-vision. Designed a novel process to retrieve CAD models and iteratively orient and align them in images, utilizing the robust nature of LLMs and foundation models trained on massive-scale knowledge sources. Orchestrated multiple SotA models for CV and vision-language tasks including GroundingDINO, Segment Anything, InstructBLIP, ZoeDepth. Built custom scripts for synthetic data generation and iterative rendering in Blender, and conducted multiple experiements to evaluate retrieval and alignment accuracy, running on an A100 HPC cluster. ### Undergraduate Researcher @ Berkeley RISE Lab Jan 2021 – Jan 2022 Conducted computer vision research with Dr. Alvin Wan under Prof. Joseph Gonzalez. Researched using temporal Neural Radiance Fields (NeRFs) for novel-view synthesis and generation of unseen vehicle trajectories from existing images captured by self-driving vehicles. Additionally researched using panoramic stitching to improve efficiency of multi-view computer vision for self-driving vehicles. ### Senior Advisor @ Berkeley Consulting Jan 2022 – Jan 2022 ### Project Manager @ Berkeley Consulting Jan 2021 – Jan 2021 Led a consulting team for a technical project in the movie industry. ### Consultant @ Berkeley Consulting Jan 2020 – Jan 2021 Consulted for multiple companies in various industries including video games, pharmaceuticals, and politics. ### Undergraduate Student Instructor for CS 170: Efficient Algorithms @ University of California, Berkeley Jan 2020 – Jan 2022 Taught multiple weekly discussion sections to supplement students' learning from professors' lectures. Taught hundreds of students, helped plan exam and homework questions, and collaborated with course staff to plan the direction of the course. ### Software Engineer Intern @ Scale AI Jan 2021 – Jan 2021 Designed and developed a character-level OCR system using state-of-the-art deep learning and computer vision techniques for a key customer project. ### Director and Tech Team Lead @ Cal Hacks Jan 2018 – Jan 2021 | Berkeley, CA Took charge of judging at Cal Hacks 5.0, gathering judges, deciding judging criteria, and managing the judging expo. Currently working as the tech lead, managing the entirety of the tech projects for Cal Hacks, while continuing charge with judging, and working on sponsorship to gather funding for the event from companies around the world. ### Siri Intern @ Apple Jan 2020 – Jan 2020 - Developed emergency contact calling functionality and additional accessibility features for Siri on iOS devices (shipped in iOS 14.5) - Managed project from start to finish, communicating with NL, design, Health, and QA testing teams to plan and implement the feature in the Siri codebase. - Coded in Swift, Objective-C, and Java. ### Undergraduate Researcher @ Berkeley RISE Lab Jan 2019 – Jan 2020 | Berkeley, CA Researched the applications of deep learning on database systems with Dr. Zongheng Yang under Prof. Ion Stoica. ### Course Reader for CS170: Efficient Algorithms @ University of California, Berkeley Jan 2020 – Jan 2020 ### Cloud Software Engineering Intern @ VMware Jan 2019 – Jan 2019 | Palo Alto, CA ### Summer Intern @ Vizru, Inc. Jan 2018 – Jan 2018 | San Jose, California Built and designed a setup for a chatbot system that works as a local substitute for DialogFlow. The system can parse intents, catch entities, and branch into a fully customizable and user-friendly dialog flow that clients can organize and setup for their own individiual needs and circumstances. The system can support multiple languages and parse a single query with multiple datasets to allow one message to be used in multiple different contexts at the same time to drastically improve efficiency. ### Technical Intern @ ON.Lab Jan 2017 – Jan 2017 Worked on two projects at ON.lab, while learning more about network infrastructure and software-defined networking in the process. The first project, net-collector, was a network monitoring system that checked internet traffic for visits to unproductive sites. If the traffic to said sites exceeded a threshold, the system alerted employees. This project served as a proof-of-concept of the use of gNMI, a network management interface using Google's open-source framework, gRPC. We used gNMI to communicate between different devices in the monitoring system, such as probes and collectors. The second project, LinkProps, enabled a user to view the link speed of, total traffic through, and the maximum bandwidth of links between devices in a network using ON.lab's open-source OS, ONOS. ### IT Intern @ TiVo Jan 2016 – Jan 2016 | San Jose Wrote testing scripts in Java for TiVo APIs. Also set up a program that tested multiple TiVo API's and constructed an html page that displayed the results and other information for each API test. Created a program that recorded the screen during website tests involving Selenium. ## Education ### Master of Philosophy - MPhil in Machine Learning and Machine Intelligence University of Cambridge ### Bachelor of Arts - BA in Computer Science University of California, Berkeley ### Bachelor of Science - BS in Business Administration University of California, Berkeley, Haas School of Business ### High School Diploma Gunn High School ## Contact & Social - LinkedIn: https://linkedin.com/in/adnaansachidanandan - Website: https://adnaan.co --- Source: https://flows.cv/adnaan JSON Resume: https://flows.cv/adnaan/resume.json Last updated: 2026-04-05