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I'd need to be convinced that they had a really interesting problem, one that would keep me awake at night. I'd also need to be convinced they understand the idea that "anything we can solve by throwing money at the problem isn't a real problem". Real problems can't be solved by money and problems that can be solved by money aren't real. You'll find at a job that a 70% productive day is outstanding. Time not lost to meetings, travel, etc. is rare. Working from home helps because it extends the work time and minimizes the interruptions. My years working from home were the most productive. As for the 70 hours thing, I work 7 days a week. Since I have no outside constraints the term 'day' gets a bit blurry; sleep happens when it happens, eating happens between keystrokes, etc. In fact, I'm "on vacation" this week at the Outer Banks but reading a PhD thesis. My wife can't understand why I brought "work" to a beach resort. She works in medicine so this really is "escape time from work" for her. Interesting work is its own motivation. We seem to have lost that idea somewhere. Her work is not interesting so she needs to escape. Mine is interesting and I consider not working as "lost time". Andrew has the possibility of "interesting work" but I'm going to bet they screw it up with things like "required sensitivity training", meetings, "required plans and schedules", "interviewing new employees", "friday lunch gatherings", skip-level interviews, open-plan floor office space, investor presentations, morning standups, on-call phone coverage, skype meetings, slack interruptions, agile card games, progress reports, company security protocols, random phone calls, trip reports, trip refund paperwork, employee ratings, changing goals, offsite meetings, time tracking, parking issues, pair programming, etc. All of which are examples of time-sinks I've experienced on the job. I can't spend 3 weeks absorbing a relevant PhD thesis "between meetings". I can't write really difficult programs without huge blocks of uninterrupted time. |
"Since we're an early stage company, you should be flexible in your tasks and do whatever is needed, ranging from dirty work like data cleaning, to high-level work like algorithm design."