Kevin S.

Key Skills

Software

Don't disclose

Top Subject Matter

Privacy-preserving federated learning and distributed ML training systems

Distributed ML training pipelines

Orchestration Domain Expertise

Top Data Types

Computer Code Programming

Text

Document

Top Task Types

Fine-tuning

Freelancer Overview

Senior Software Engineer — Privacy-preserving federated learning and distributed model training (RTX Corporation). Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Bachelor of Science, Tufts University (2016). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Fine-tuning.

Labeling Experience

Senior Software Engineer — Privacy-preserving federated learning and distributed model training (RTX Corporation)

Don't discloseFine-tuning

Developed privacy-preserving federated learning services and distributed client trainers to enable large model experimentation. Implemented metric aggregation for training loss, accuracy, client participation, communication latency, and resource utilization to support training performance evaluation. Optimized training communication using gradient compression and asynchronous aggregation to reduce bandwidth overhead. • Built Flask/WSGI REST monitoring dashboards • Integrated Weights & Biases (WandB) for experiment tracking across federated environments • Deployed inference services with Ray and vLLM on Kubernetes • Refactored ML orchestration modules and automated CI/CD workflows for reproducible training

2022 - 2025

Software Engineer — Distributed model training pipelines and ML workflow orchestration (Optimus Ride)

Don't discloseFine-tuning

Engineered distributed model training pipelines using Python and PyTorch in GPU-enabled HPC environments. Built backend orchestration services with Flask/WSGI and designed dashboards to monitor training progression, queue times, and hardware utilization. Integrated experiment tracking and observability using WandB and telemetry collectors to support iterative AI training. • Implemented scalable container orchestration with Docker and Kubernetes • Built CI/CD reliability improvements via automated test suites • Created cloud-native data ingestion pipelines across AWS EC2, S3, and EKS • Developed REST APIs exposing real-time system metrics and federated coordination events

2017 - 2022

Education

Work History