Process
The interview process was not quite the most optimal or mutually beneficial. All interviews had a "tricky" part to them, whether trying to validate the person or the skills.
Few interviewers were quite young with only a few years of experience, and I could sense they wanted me to rush and quickly get to the solution.
During the coding round, the girl interviewing me was getting impatient with me asking questions and even told me to just get to the implementation fast.
Questions
DSA, HashMaps, stacks, heaps, queues, and basic system design questions. You just need to be able to read the mind of the interviewer pretty well.
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Interview Statistics
The following metrics were computed from 3 interview experiences for the Snorkel AI Software Engineer role in United States.
Success Rate
0%
Pass Rate
Snorkel AI's interview process for their Software Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive33%
Neutral33%
Negative33%
Candidates reported having mixed feelings for Snorkel AI's Software Engineer interview process in United States.
Snorkel AI Work Experiences
4.0
Figuring out direction
Software Engineer • Current Employee
San Francisco, CA
October 28, 2025
Pros: There are talented and driven people at the company, and you will learn a lot working here.
Cons: The company is trying to pivot, and there is a lot of chaos currently.
5.0
Some of the most talented and empathetic people in the world
Software Engineer • Current Employee
San Francisco, CA
August 18, 2021
Pros: - Very intelligent teammates who have an immense depth of knowledge in their domain
- Lots of different interesting projects to work on, and it is easy to move between projects
- Upper management drilled down an empathetic work culture that helps create one of the least antagonistic and friendly workplaces I have seen
Cons: - Some managers are software engineers who de-facto became managers and lack experience being managers. They are trying their best though!
- Not everything is set in stone yet so you might need to ask for things that may be normal at other companies.
2.0
Pivot to oblivion
Software Engineer • Former Employee
Redwood City, CA
November 1, 2025
Pros: - Good engineering and research talent.
- Good people to work with.
- Decent place to learn about AI, or at least it used to be.
- Good middle-management, reasonable expectations and perf reviews.
- Good reputation in the industry that can be a good stepping stone to something else, or as a foot in the door of the AI industry.
- Cool swag and events.
Cons: - Immature executive leadership who let their Stanford PhD reputations carry them
- Despite what they say, they don't care about their people; this is obvious when someone leaves, voluntarily or not. Outside their immediate pod, they tend to just disappear. Only longer tenured employees get a mention, typically in a random Slack message. Otherwise, you find out by suddenly finding them deactivated on Slack without any explanation
- Poor strategy and long term decision making that was very slow to react to the rapid swing towards gen-AI, and then it was way too little too late
- Core business, which seemed very promising, dried up
- Dramatic pivot to new data as a service direction of which is not what anyone signed up for, and they're essentially working 9-9-6. Working so intensely, they're doing nothing but creating engineering tech-debt, and never cleaning any of it up.
- Super competitive market for the new direction, and they're extremely far behind already. Very unlikely they can catch up
- Work is uninteresting, just grinding - especially post-pivot
- Aimless design efforts
- 4.0Figuring out directionSoftware Engineer • Current EmployeeSan Francisco, CAOctober 28, 2025Pros: There are talented and driven people at the company, and you will learn a lot working here.Cons: The company is trying to pivot, and there is a lot of chaos currently.
- 5.0Some of the most talented and empathetic people in the worldSoftware Engineer • Current EmployeeSan Francisco, CAAugust 18, 2021Pros: - Very intelligent teammates who have an immense depth of knowledge in their domain - Lots of different interesting projects to work on, and it is easy to move between projects - Upper management drilled down an empathetic work culture that helps create one of the least antagonistic and friendly workplaces I have seenCons: - Some managers are software engineers who de-facto became managers and lack experience being managers. They are trying their best though! - Not everything is set in stone yet so you might need to ask for things that may be normal at other companies.
- 2.0Pivot to oblivionSoftware Engineer • Former EmployeeRedwood City, CANovember 1, 2025Pros: - Good engineering and research talent. - Good people to work with. - Decent place to learn about AI, or at least it used to be. - Good middle-management, reasonable expectations and perf reviews. - Good reputation in the industry that can be a good stepping stone to something else, or as a foot in the door of the AI industry. - Cool swag and events.Cons: - Immature executive leadership who let their Stanford PhD reputations carry them - Despite what they say, they don't care about their people; this is obvious when someone leaves, voluntarily or not. Outside their immediate pod, they tend to just disappear. Only longer tenured employees get a mention, typically in a random Slack message. Otherwise, you find out by suddenly finding them deactivated on Slack without any explanation - Poor strategy and long term decision making that was very slow to react to the rapid swing towards gen-AI, and then it was way too little too late - Core business, which seemed very promising, dried up - Dramatic pivot to new data as a service direction of which is not what anyone signed up for, and they're essentially working 9-9-6. Working so intensely, they're doing nothing but creating engineering tech-debt, and never cleaning any of it up. - Super competitive market for the new direction, and they're extremely far behind already. Very unlikely they can catch up - Work is uninteresting, just grinding - especially post-pivot - Aimless design efforts
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