Remote: Prefer in-person, but happy to work remotely.
Willing to relocate: Yes, within APAC region.
Technologies: Mostly Python (SciPy stack for data science & scikit-learn for machine learning) and R for data science; experience with declarative languages like Haskell, Prolog, and SQL. Experience with Go, Java, some Rust and C++. Comfortable in a UNIX environment/shell and with writing LaTeX.
TL;DR: 1.5 years of experience in consulting/financial services and graduating from postgrad computer science degree in November. Seeking roles that will stretch my technical skills to work on interesting, meaningful problems (e.g. research, finance, data science, etc.).
Hi there!—I'm Jack. My academic background is in computer science (currently writing my minor thesis in computational modelling & simulation; set to graduate in November) and I currently work for a Big 4 consulting & financial services company (~1.5 years of experience). As an intern, I helped save my team ~4 weeks of manual work because I insisted on creating a parser for messy log files generated by a client's old COBOL scripts. When I returned as a full-time employee, I spotted an opportunity to automate the analysis of credit risk impacts, and used the software to help a large telecommunications company with 5M+ customers. I love puzzles, and my specialty is using statistical and computational techniques to solve them. As I approach the end of my postgrad degree, I'm in search of technical opportunities to work on interesting problems alongside inquisitive folks, preferably in Melbourne/Australia. Please feel free to reach out!
Take for example their recent addition to the desktop app called "Now playing view" which opens every time you play a song (unless you disable it), squishes your current view into a three-pane window, and displays valuable information such as the song's album cover, which is already on the screen in the lower-left corner!
Because you need a reliable way to convert human speech into a structured representation of actions that the smart device can execute so the LLM can interface with the underlying system. For most smart devices this is probably locked away, and combined with issues like hallucination, lack of training data for the action representation, etc., it's hard to say whether such technology would be reliable enough for stable use.
We've seen a similar thing with big companies putting in LLM chatbots for customer service -- turns out LLMs can go off the rails really easily with the right prompts.
Remote: Prefer in-person, but happy to work remotely.
Willing to relocate: Yes, within APAC region.
Technologies: Mostly Python (SciPy stack for data science & scikit-learn for machine learning) and R for data science; experience with declarative languages like Haskell, Prolog, and SQL. Experience with Go, Java, some Rust and C++. Comfortable in a UNIX environment/shell and with writing LaTeX.
Résumé/CV: https://blademaw.github.io/features/files/cv.pdf
Email: Please see top of CV (link above).
TL;DR: 1.5 years of experience in consulting/financial services and graduating from postgrad computer science degree in November. Seeking roles that will stretch my technical skills to work on interesting, meaningful problems (e.g. research, finance, data science, etc.).
Hi there!—I'm Jack. My academic background is in computer science (currently writing my minor thesis in computational modelling & simulation; set to graduate in November) and I currently work for a Big 4 consulting & financial services company (~1.5 years of experience). As an intern, I helped save my team ~4 weeks of manual work because I insisted on creating a parser for messy log files generated by a client's old COBOL scripts. When I returned as a full-time employee, I spotted an opportunity to automate the analysis of credit risk impacts, and used the software to help a large telecommunications company with 5M+ customers. I love puzzles, and my specialty is using statistical and computational techniques to solve them. As I approach the end of my postgrad degree, I'm in search of technical opportunities to work on interesting problems alongside inquisitive folks, preferably in Melbourne/Australia. Please feel free to reach out!