
The Jane Street Interview Process — 2020 Edition
The blogpost discusses the updated and transparent interview process for software engineering candidates at Jane Street in 2020, including changes made due to COVID-19.

DeveloperBridge: SoundCloud’s Program for Training People from Diverse Backgrounds to Become Engineers
A year-long, full-time, paid traineeship program for training people from diverse backgrounds to become engineers by learning from and working with engineering teams at SoundCloud.

OpenAI Scholars 2020: Final projects
Discover the innovative final projects of OpenAI Scholars 2020 cohort.

Changing the Interview Process during Remote Working
Changing the interview process and its challenges in a remote work setting.

Technical Interview Reform, Part 2: The Recruiting Perspective and Results
The blogpost discusses the recruiting perspective and results of technical interview reform, as a follow-up to Part 1 which focused on rethinking the backend engineering interview take-home challenge.

Technical Interview Reform, Part 1: Rethinking the Backend Engineering Interview Take-Home Challenge
Reforming the backend engineering interview process by rethinking the take-home challenge

RL Unplugged: Benchmarks for Offline Reinforcement Learning
A proposal for a benchmark called RL Unplugged to evaluate and compare offline RL methods with diverse datasets from various domains.

Applying for technical roles
Addressing the gender gap in the STEM workforce and providing guidance for women on applying for technical roles.

Really low latency multipliers and cryptographic puzzles
Exploring the use of FPGAs for low-latency systems and the increased accessibility of renting FPGA cards on the cloud

Procgen and MineRL Competitions
Exploring the latest advancements in procedural generation and MineRL competitions

Image GPT
Exploring the innovative capabilities of Image GPT for enhanced visual understanding.

dm_control: Software and Tasks for Continuous Control
A collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation, with convenient bindings, procedural model manipulation, and task authoring.