> ./hire_me.sh | Faiz Palwala

resume.pdf
[email][linkedin][github][huggingface]

I am Faiz Palwala, an AI/ML Engineer. I spent four years at Deloitte architecting cloud infrastructure and microservices at scale, then completed an MSc in Advanced Computer Science (AI) at the University of Leeds. Now I build ML systems end to end: SFHQ-VirtualID, a public benchmark dataset for machine unlearning from my MSc dissertation; GraphContext MCP, a local-inference structural parser for AI coding agents; and Breadwinner, an LLM tool grounded in verified data instead of guesswork. My focus: infrastructure that makes ML systems provably reliable, not just functional.

Open to ML Engineer, MLOps, and Software Engineer roles in the UK, EU, or remote.

## Skills

[CORE]
PythonJavaGoJavaScript/TypeScriptSQLGit
[ML/AI]
PyTorchHugging FaceDiffusersLLMsRAG (Vertex AI)Prompt EngineeringCUDA
[DATA/INFRA]
PostgreSQLMongoDBRedisElasticsearchGraphQLMicroservices
[CLOUD]
AWSDockerCI/CDJenkins

## Experience

Software Development Engineer 2 @ Deloitte

Apr 2023 - Sept 2024 | Bengaluru, IN

  • Enterprise Platform Stabilisation: Spearheaded pre-MVP stabilisation across 3 core healthcare products. Delivered 100+ end-to-end features and resolved 20 critical production incidents across 14 release cycles. Served as the sole Technical SME for the Benefit Determination platform.
  • Technical Leadership: Mentored and directed a 3-person agile engineering pod. Established secure coding standards and technical knowledge-sharing (KT) protocols, earning 2x Applause Awards for outstanding leadership.
  • Process Optimisation (TCH Bypass): Architected and deployed a Proof of Concept workflow enabling operators to bypass systemic TCH errors. Recovered 90%+ of unworkable claims and drove a 40% reduction in the pended claim backlog.
  • Automated Data Remediation: Engineered Python-based database utility scripts to automate the generation of data remediation queries. Successfully processed 3M+ inbound records and reconciled 1.6M+ historical data anomalies, significantly improving data integrity.

Software Development Engineer @ Deloitte

Jul 2020 - Apr 2023 | Bengaluru, IN

  • High-Scale Systems Development: Core engineer on the HCSC Claims Modernisation Platform, building distributed backend solutions to serve 23M+ members across 5 US states. Recognized with 4x Spot Awards and 2x Applause Awards for exceptional delivery.
  • Core Microservices: Architected and implemented critical business logic (adjustments, alternates, manual load, NSA) across 7 Spring Boot microservices.
  • Quality & Delivery: Shipped 120+ complex features and defect resolutions across 20+ sprint cycles. Enforced rigorous engineering standards, maintaining 90%+ code coverage through comprehensive JUnit testing suites.
  • DevOps & Reliability: Orchestrated CI/CD deployment pipelines using Jenkins across 4 major production releases. Acted as a first responder for production incidents, utilizing Dynatrace for deep log analysis and rapid hotfix deployment.

Preceded by a 6-month SDE Internship (Jan-Jul 2020) on the same team, reliability fixes across core microservices.

Information Security Intern @ Gap Inc.

May 2019 - Jul 2019 | Hyderabad, IN

  • Workflow Automation: Identified critical inefficiencies in the Asset Management lifecycle and engineered an automated Configuration Management Database (CMDB) interface leveraging ReactJS and Elasticsearch.
  • Security & Compliance: Embedded within the Data Protection Team to execute security workflows, gaining applied expertise in Vulnerability Management and Enterprise Endpoint Security within Gap's global security stack.

## Education

MSc Advanced Computer Science (AI)

University of Leeds | 2025 - 2026

Dissertation: evaluated 11 machine-unlearning methods on SFHQ-VirtualID (750 identities). Fine-tuning reached oracle-grade erasure (MIA AUC 0.0004, statistically indistinguishable from a full retrain) at a fraction of the cost; only retain-regularised methods survived 15 sequential deletion requests. Full write-up on /research.

B.Tech Computer Science and Engineering

VIT Vellore | 2016 - 2020

CGPA: 8.35. Coursework: AI, NLP, Parallel and Distributed Computing.

## Certifications & Awards

[CERTIFICATIONS]
  • Java SE 11 Developer Professional (1Z0-819), Oracle, 2023
  • AWS Certified Cloud Practitioner, Amazon Web Services, 2022
[AWARDS]

Best Alexa Implementation (CSI, VIT Chapter, 2019) · Applause Award x2 (Deloitte) · Spot Award x4 (Deloitte)

## Featured Work

[project]

SFHQ-VirtualID: Synthetic Identity Datasets for Machine Unlearning

A reproducible pipeline that generates synthetic, identity-conditioned face clusters, released as a citable, identity-level benchmark for machine unlearning.

[project]

GraphContext MCP

A privacy-first macOS application that acts as a structural brain for AI coding assistants using deterministic parsing and local MLX models.

[project]

Serverless GitHub Calendar

A 100% reliable, zero-runtime-dependency GitHub Contribution Heatmap architecture built for React and static sites.

[research]

SFHQ-VirtualID-Bench: Identity-Level Machine Unlearning Benchmark

Identity-level machine unlearning benchmark: 750 identities, each one a deletion unit, with uniform and long-tail forget schedules.

[noggin]

SFHQ-VirtualID is public: 750 synthetic identities, each one a deletion unit

The embargo lifted: SFHQ-VirtualID is now public on Hugging Face, with Zenodo DOIs ready for citation.

Full list: projects · research · noggin.

## Get In Touch

Open to ML Engineer, MLOps, and Software Engineer roles in the UK, EU, or remote.

[email][linkedin][github][huggingface][resume.pdf]

Faiz Palwala

AI/ML Engineer

faiz.palwala@gmail.com  |  linkedin.com/in/faizpalwala  |  github.com/FaizPalwala  |  huggingface.co/FaizPalwala

SUMMARY

Faiz Palwala is an AI/ML Engineer. He spent four years at Deloitte architecting cloud infrastructure and microservices at scale, then completed an MSc in Advanced Computer Science (AI) at the University of Leeds. He now builds ML systems end to end: SFHQ-VirtualID, a public benchmark dataset for machine unlearning from his MSc dissertation; GraphContext MCP, a local-inference structural parser for AI coding agents; and Breadwinner, an LLM tool grounded in verified data instead of guesswork. Open to ML Engineer, MLOps, and Software Engineer roles in the UK, EU, or remote.

SKILLS

CORE  PythonJavaGoJavaScript/TypeScriptSQLGit
ML/AI  PyTorchHugging FaceDiffusersLLMsRAG (Vertex AI)Prompt EngineeringCUDA
DATA/INFRA  PostgreSQLMongoDBRedisElasticsearchGraphQLMicroservices
CLOUD  AWSDockerCI/CDJenkins

EXPERIENCE

Software Development Engineer 2, Deloitte Apr 2023 to Sept 2024 | Bengaluru, IN

  • Enterprise Platform Stabilisation: spearheaded pre-MVP stabilisation across 3 core healthcare products. Delivered 100+ end-to-end features and resolved 20 critical production incidents across 14 release cycles. Sole Technical SME for the Benefit Determination platform.
  • Technical Leadership: mentored and directed a 3-person agile engineering pod. Established secure coding standards and technical knowledge-sharing protocols, earning 2x Applause Awards for outstanding leadership.
  • Process Optimisation (TCH Bypass): architected and deployed a proof-of-concept workflow enabling operators to bypass systemic TCH errors. Recovered 90%+ of unworkable claims and drove a 40% reduction in the pended claim backlog.
  • Automated Data Remediation: engineered Python-based database utility scripts to automate the generation of data remediation queries. Processed 3M+ inbound records and reconciled 1.6M+ historical data anomalies.

Software Development Engineer, Deloitte Jul 2020 to Apr 2023 | Bengaluru, IN

  • High-Scale Systems Development: core engineer on the HCSC Claims Modernisation Platform, building distributed backend solutions serving 23M+ members across 5 US states. Recognized with 4x Spot Awards and 2x Applause Awards.
  • Core Microservices: architected and implemented critical business logic (adjustments, alternates, manual load, NSA) across 7 Spring Boot microservices.
  • Quality and Delivery: shipped 120+ complex features and defect resolutions across 20+ sprint cycles, maintaining 90%+ code coverage through JUnit testing suites.
  • DevOps and Reliability: orchestrated CI/CD deployment pipelines using Jenkins across 4 major production releases; first responder for production incidents using Dynatrace.

Preceded by a 6-month SDE Internship (Jan to Jul 2020) on the same team.

Information Security Intern, Gap Inc. May 2019 to Jul 2019 | Hyderabad, IN

  • Workflow Automation: identified inefficiencies in the Asset Management lifecycle and engineered an automated CMDB interface using ReactJS and Elasticsearch.
  • Security and Compliance: embedded within the Data Protection Team executing security workflows across Gap's global security stack.

EDUCATION

MSc Advanced Computer Science (AI), University of Leeds2025 to 2026

Dissertation: evaluated 11 machine-unlearning methods on SFHQ-VirtualID (750 identities). Fine-tuning reached oracle-grade erasure (MIA AUC 0.0004, statistically indistinguishable from a full retrain) at a fraction of the cost; only retain-regularised methods survived 15 sequential deletion requests.

B.Tech Computer Science and Engineering, VIT Vellore2016 to 2020

CGPA: 8.35. Coursework: AI, NLP, Parallel and Distributed Computing.

CERTIFICATIONS AND AWARDS

Certifications: Java SE 11 Developer Professional (1Z0-819), Oracle, 2023; AWS Certified Cloud Practitioner, Amazon Web Services, 2022.

Awards: Best Alexa Implementation (CSI, VIT Chapter, 2019); Applause Award x2 (Deloitte); Spot Award x4 (Deloitte).

FEATURED WORK

SFHQ-VirtualID: Synthetic Identity Datasets for Machine Unlearning: A reproducible pipeline that generates synthetic, identity-conditioned face clusters, released as a citable, identity-level benchmark for machine unlearning.

GraphContext MCP: A privacy-first macOS application that acts as a structural brain for AI coding assistants using deterministic parsing and local MLX models.

Serverless GitHub Calendar: A 100% reliable, zero-runtime-dependency GitHub Contribution Heatmap architecture built for React and static sites.

SFHQ-VirtualID-Bench: Identity-Level Machine Unlearning Benchmark: Identity-level machine unlearning benchmark: 750 identities, each one a deletion unit, with uniform and long-tail forget schedules.