Ajit Jadhav

Software Engineer

San Francisco, California, United States3 yrs 8 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in full stack development with a focus on user experience.
Proven track record in leading complex software projects.
Strong background in machine learning and AI applications.

Stackforce AI infers this person is a Fullstack Software Engineer with expertise in AI and consumer electronics.

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Skills

Core Skills

ReactDistributed SystemsDjangoMachine LearningNlpDatabase ManagementData Management

Other Skills

Developer ToolingUser ExperienceAnalyticsMonitoring ToolsML InfrastructureChatbot DevelopmentDeployment WorkflowsData IngestionMicroservicesBibliographic Data ManagementSQLHTMLCSSData ScienceVirtual Machines

About

I’m a software engineer who enjoys owning projects end-to-end—from shaping the initial idea and technical design to shipping, operating, and iterating in production. I’ve worked across the full stack, building user-facing interfaces, backend services, data pipelines, and distributed systems, with a strong focus on reliability, performance, and maintainability. I work closely with product managers, designers, and stakeholders to turn ambiguous requirements into clear, high-impact solutions, and I’m comfortable leading projects by driving scope, making trade-offs, and unblocking progress. I’m motivated by environments where engineers have real ownership, collaborate deeply across disciplines, and build systems that create meaningful value for users and the business.

Experience

3 yrs 8 mos

Total Experience

11 mos

Average Tenure

1 yr

Current Experience

Amazon

Software Engineer

Jun 2025 – Present · 1 yr · Sunnyvale, California, United States · On-site

As part of the Alexa Endpoint Experiences team:
Worked on distributed, on-device systems and developer tooling for Alexa Home Theater
Shipped a low-latency audio coordination system used at large scale and built internal schema and configuration tools that improved developer productivity
Led development of a React-based onboarding experience for customer device setup.

Distributed SystemsDeveloper ToolingReact

Spot & tango

Software Engineer

Jan 2024 – Jun 2025 · 1 yr 5 mos · New York, New York, United States · Hybrid

As part of a 4-member tech team:
Built customer-facing and internal product features across the full stack using React and Django
Delivered performance-focused checkout and onboarding improvements, discount and campaign systems, and analytics-driven event tracking that increased conversion and engagement

ReactDjangoAnalytics

Uc santa barbara

Graduate Teaching Assistant

Sep 2021 – Aug 2023 · 1 yr 11 mos

Automationedge

Software Engineer

Sep 2020 – Apr 2021 · 7 mos · Remote

As part of the data science and development team (a new small division of 5 team members):
Developed NLP chatbot training and deployment platforms, including end-to-end training pipelines and internal frontend tools for dataset and label management. Automated enterprise deployment workflows and supported customer onboarding for AI-driven support solutions.

NLPChatbot DevelopmentDeployment Workflows

Google summer of code

Software Engineer Intern

Jun 2020 – Aug 2020 · 2 mos

Developed and deployed a comprehensive bibliographic data management system to facilitate seamless access and modification of research and artifact data for Cuneiform text researchers

Bibliographic Data ManagementData Management

Cuneiform digital library initiative

Open Source Contributor

Jan 2020 – Dec 2020 · 11 mos

Automated data ingestion and created features for admin managed display of data, and resolved issues in the database for the development of the new framework for managing and viewing artifacts and related data
Worked on creating Docker containers to split the system into a microservice architecture

Data IngestionMicroservicesDatabase Management

Indian institute of technology, delhi

Research Intern

May 2019 – Jul 2019 · 2 mos · Delhi

Gained a 19% improvement in the mean Average Precision score for drone object detection by devising a novel implementation of deep association networks
Tackled problems like large variation in object sizes, dense object distribution, and insufficient training data for drone-based applications by surveying and improving the shortcomings of existing methods
Secured 8th rank in the ICCV VisDrone2019 challenge by devising a multi-object tracking model for drones
Published the research findings in the 2020 National Conference on Communications (NCC)