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ML ♥️ Infrastructure.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
openharness
April 12, 2026 – Present
Pluggable runtime for building LLM agents with swappable runners, stores, tools, secrets, artifacts, and channels
View Projectrust-grpc-example
September 19, 2020 – May 2, 2022
A minimal Rust based gRPC client and server (using tonic-rs)
View Projectbeam-rust
September 18, 2020 – September 18, 2020
Rust library based for Apache Beam. Based on Beam's new portability framework
View Projectrust-protobuf-example
April 19, 2020 – April 20, 2020
rust-protobuf-example — GitHub repository
View Projectkfctl-action
October 30, 2019 – January 4, 2023
Action to install Kubeflow on Kubernetes clusters
View Projectdl-kops
December 17, 2017 – August 21, 2018
Simple. Cloud Native. Machine Learning. Kubernetes. Infrastructure. GPUs.
View Projectkube-gpu-scheduler
September 23, 2017 – October 4, 2017
A multi-user scheduler for GPU, CPU clusters.
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards infrastructure, systems programming, and MLOps, which aligns with a data scientist role that involves deploying and managing models. However, the lack of traditional data science projects (e.g., data analysis, model building, statistical modeling) suggests a potential gap in core data science skills. The diversity of technologies (Rust, Go, Python, JavaScript, Shell) indicates adaptability, but the focus is heavily on backend/infrastructure.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are brief, limiting insight into collaboration or problem-solving approaches.