Rishabh Sood

Software Engineer

India2 yrs 9 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in Machine Learning and AI technologies.
Proven track record in optimizing complex systems.
Strong background in backend development and DevOps.

Stackforce AI infers this person is a Backend-heavy Fullstack Engineer with expertise in Machine Learning and AI solutions.

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Skills

Core Skills

Machine LearningArtificial IntelligenceKubernetes

Other Skills

DeepspeedSupervised FineTuningRetrieval-Augmented Generation (RAG)gRPCCI CDDockerGolangPrometheusGrafanaRust (Programming Language)GraphRAGKnowledge Graph-Based Natural Language ProcessingLarge Language Models (LLM)Spring FrameworkJava

About

Hi! I am Rishabh Sood, a highly motivated Software Development Engineer with a solid foundation in the field of Computer Science. Having garnered valuable experience through internships at both Apple and Goldman Sachs, I currently contribute my skills as a Software Engineer at Apple. My expertise spans across backend development, DevOps, and the dynamic domains of Machine Learning and Artificial Intelligence. Passionate about delivering swift, cost-effective technology solutions, I thrive on navigating new challenges in the ever-evolving landscape of computer science. With a steadfast mission to continually enhance my skills and contribute to groundbreaking technology, I am open to networking and enthusiastic about collaborating on future innovations in the tech industry.

Experience

2 yrs 9 mos

Total Experience

1 yr 4 mos

Average Tenure

2 yrs 4 mos

Current Experience

Apple

Software Engineer

Jan 2024 – Present · 2 yrs 4 mos · India · On-site

1. Support App Chat (Generative Experience):  Contributed to the development of one of Apple’s first generative multi-turn conversational experiences for customer support.
◦ Impact
Co-developed a multi-agentic architecture with tool-calling capabilities, enabling the system to perform complex actions like checking warranty status, scheduling repairs, and querying knowledge base articles in real-time.
Engineered a robust Retrieval-Augmented Generation (RAG) pipeline to ground the model’s responses in Apple’s proprietary knowledge base, reducing hallucinations and increasing factual accuracy.
Focused heavily on system safety and reliability, implementing guardrails and content filters to ensure all generated responses aligned with Apple’s brand and quality standards.
Directly impacted the customer experience for millions of users by providing an instant, 24/7 conversational support channel within the Apple Support app.
2. Apple Developer Search:  Engineered geographical expansion of Apple Developer Search to multiple regions / languages, while keeping the search experience consistent.
◦ Impact
Added support for developer search across multiple regions, overcoming the language barrier previously inhibiting user experience consistency on the developer website.
Optimized storage costs to a tenth (1/10) without compromising on the quality of search results.
3. Knowledge Hub:  Engineered & Architected a Data extraction - transformation - storage pipeline to centralize all data related operations in the team. Furthermore integrating with intelligent search / manipulation APIs to perform operations on the stored data.
◦ Impact
Custom plugin architecture supporting dynamic pipeline structuring. (Data Sources: Message Queues / APIs etc.; Transformation: Cleaning, Chunking, Embedding etc.; Storage: Vector DBs, RDBs etc.
Centralized management with unified - consistent data pipelines.

DeepspeedSupervised FineTuningRetrieval-Augmented Generation (RAG)gRPCMachine LearningArtificial Intelligence

Goldman sachs

Engineering Analyst

Jul 2023 – Dec 2023 · 5 mos · India · On-site

1. Internal App Store
Delivered a comprehensive overhaul of the organization's central App Store, impacting every user.
◦ Impact:
Successfully migrated the entire App Store architecture from Windows server deployment to Kubernetes, optimizing scalability and efficiency.
Introduced a regression test suite, automating UAT environment testing to preemptively catch bugs and eliminate manual, error-prone testing procedures.
Implemented new features including the creation of software bundles and version rollback, enhancing the overall user experience and functionality.
2. Data Aggregator
Led the development of a versatile data aggregator, facilitating seamless extraction, transformation, and merging of data from diverse sources into a staging area for efficient data lake onboarding.
◦ Impact:
Architected a highly configurable system, automating Kubernetes job scheduling based on user-defined configurations.
Significantly reduced costs compared to traditional Windows server deployments within the team.

KubernetesCI CD

Apple

Software Engineer

Jan 2023 – Jun 2023 · 5 mos · India · On-site

1. Enhanced Apple Support Chat Experience:
Developed an Intelligent Recommendation Service using the dynamic Apple Support Knowledge Base (real-time sync), reducing response time from minutes to a fraction of a second.
◦ Impact
Improved user support by integrating generative responses and sentiment analysis in test phase for personalized and empathetic interactions.
◦ Future Prospects
Reduced reliance on live agent support post integration and expanding usage across other platforms for efficient query resolution.
2. Innovated a Centralized Package:
To reduce redundancy, streamline code and enhance productivity across team repositories.
◦ Impact
Improved code quality
Facilitated faster & flexible implementation flows for developers

KubernetesDocker

Goldman sachs

Summer Analyst

Jun 2022 – Jul 2022 · 1 mo · Bengaluru

Core Engineering
Developed & Deployed an emergency call notification service on global scale.
◦ Impact:
Replaced the legacy 3rd party vendor solution thereby saving USD 35K-40K per annum for the company.
Successfully delivered emergency call notifications to the security team in real time.
Extendable to new regions with ease.
◦ Tech-Stack: Golang, Kubernetes, Prometheus (Metrics & Alerting), Grafana, Fluentbit, BigQuery, Docker, Gitlab CI-CD Pipelines, SRE.

KubernetesDocker