I'm Vitaly Chait, a software engineer working on applied AI and quantitative research. I bring ten years of engineering experience, including software development at NeuroBlade in Tel Aviv and systems engineering at KLA in Israel and Beijing. I'm completing an MS in Business Analytics at Brandeis University, where I also support generative AI teaching and research.
Engineering and research roles in the US, Israel, and China.
Brandeis University
Massachusetts, United States
Working across artificial intelligence, PyTorch, teaching, and technical leadership while supporting BUS 244A: Generative AI Foundations for Business under Professor Shubhranshu Shekhar.
NeuroBlade
Tel Aviv-Yafo, Israel | Hybrid
Self-employed | Freelance
Beijing, China | Remote
Designed and deployed custom applications for SoC-based products and machine learning solutions, using Flask for server-side development, scikit-learn for ML, and OpenCV for motion and image processing.
KLA
Tel Aviv District, Israel | On-site
KLA
Beijing, China
Bridged communication between R&D and field engineering teams, streamlining rollout processes.
Sea Center - Lev Hayam | Seasonal
Tel Aviv-Yafo, Israel
Israeli Defense Forces
Lead instructor for IDF officers.
Ankori School
Tel Aviv-Yafo, Israel | On-site
Supported students academically and personally after completing a full year of volunteering.
Prediction-market analytics, portfolio research, and LLM safety evaluation.
Prediction-market analytics
I built tracking tools for order books, transaction flows, and wallet clusters in decentralized prediction markets.
PolyGains brings market activity, wallet behavior, and trading patterns into one interface.
Explore PolyGainsOrders | Trades | Wallets
Flow analysis | Wallet clusters
Patterns | Activity | Alerts
SSGA summer research | Jun - Aug 2026
Researched a multi-asset meta-labeling portfolio pipeline in collaboration with State Street Global Advisors, associated with Brandeis School of Business and Economics.
Research project | May 2026 - Present
Researching how multi-turn evaluation can better capture evolving risks for young people in LLM-mediated social environments, beyond the limits of static safety benchmarks.
Participant and volunteer | 2025 to 2026
Participated in Sundai Club projects and volunteered at community events, including running a weekend hackathon and supporting the Sundai Anniversary event at Boston University.
Recognized at Orbotech in June 2019, selected from more than 200 employees in FPD R&D.
Tools and methods used across my engineering work and research.
Python | Java | C | C++ | Linux | Kernel programming | PCIe | FPGA diagnostics
Presto | Spark | scikit-learn | OpenCV | Data engineering | Image processing | Algorithm design
Jenkins | Git | Docker | Flask | Grafana | Prometheus | MySQL | InfluxDB | Debian packaging
Systems engineering | MATLAB | SoC | Silicon validation | EDA | Metrology | Optical imaging | LLM evaluation
I'm based in the Austin, Texas metropolitan area. My background is in software development, systems engineering, and semiconductors.
At NeuroBlade, I worked on diagnostics, Linux drivers, benchmarking, and observability. Before that, I developed applications as a freelancer and worked on system integration and optical imaging at KLA. My work has taken me to Cupertino, Shanghai, Beijing, and Tel Aviv.
I'm completing an MS in Business Analytics at Brandeis School of Business and Economics. I also work as a Graduate Research and Teaching Assistant, supporting Generative AI Foundations for Business and conducting AI research.
Outside engineering, I've taught sailing, mathematics, and English. I also spent a year volunteering with Sea Scouts, working with at-risk teenagers.
Dec 2025 - Dec 2026
Brandeis University | School of Business and Economics
MS candidate, expected December 2026.
Sep 2025 - Dec 2025
Massachusetts Institute of Technology (MIT)
Coursework through MIT Media Lab AI Venture Studio, led by Ramesh Raskar and Nikolay Vyahhi. This is a course experience, not a degree program.
Mar 2019 - Jun 2022
The Open University of Israel
Coursework in numerical analysis, data science, databases, and advanced programming.
Certifications: Jenkins and Docker, TestDome, January 2023.
Detailed pages about my background, research, engineering work, and projects.
I'm interested in software, systems, data engineering, and applied AI roles. Reach me by email or LinkedIn.