Row 43395
Content Data
This page contains data entry 43395 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
I feel like ML Engineer as a Job Title was created to fill in the gap between models created, that look promising to a given business and to actually put these models to productive work.
Then ML Engineer becomes somewhat like a unicorn: Speak statistics / python, Talk to Infra and with Infra folks / bash + Linux, Talk to app development and database ppl / java + node + all them DBs. It is a very senior role by that very definition, but how do you communicate that on a Job Posting?
I've seen companies opt for a strategy to look for what they are missing. We do not have anyone who knows "python + stats + bash + Linux"? We shall call her ML Engineer.
| Field | Value |
|---|---|
| text | I feel like ML Engineer as a Job Title was created to fill in the gap between models created, that look promising to a given business and to actually put these models to productive work. Then ML Engineer becomes somewhat like a unicorn: Speak statistics / python, Talk to Infra and with Infra folks / bash + Linux, Talk to app development and database ppl / java + node + all them DBs. It is a very senior role by that very definition, but how do you communicate that on a Job Posting? I've seen c… |
| label | r/datascience |
| dataType | comment |
| communityName | r/datascience |
| datetime | 2024-05-22 |
| username_encoded | Z0FBQUFBQm5Lak1PdUpMMVBXaVJZOFJObm02YUFqYVk0cFZmTDVDek43MWpDRF94SkpBeDM3ZFZFcDg0ZDY1TkZPNVJWODYwNVZEMzREV055VGhmOXpwdnNFZk52OUtON1E9PQ== |
| url_encoded | Z0FBQUFBQm5Lak9kanpYdkZZcjhJS250eTZvbE5wUGxOcHpjSDhIanBmQ2pJWEtFOGRTOGtBck1aU1ZkWEVfdjlJbFlseXN3NTRqVkhjUUF5dzJNRkxwRExpOUdmZE1jM1hkbFVMU3J6MzNuYzlMTXdIRGRIUWJuYk9FMXI4amNXeGlVQkdLM3Axa3pWWWJ5eGhBMTREOW1QNlFfVXNzVVplMWVobWVpYWFPazRNWl9VUjVDSGx0b09NeVRDMnkteVFjVWRSckRVUnlW |
Raw Record
{
"text": "I feel like ML Engineer as a Job Title was created to fill in the gap between models created, that look promising to a given business and to actually put these models to productive work. \n\nThen ML Engineer becomes somewhat like a unicorn: Speak statistics / python, Talk to Infra and with Infra folks / bash + Linux, Talk to app development and database ppl / java + node + all them DBs. It is a very senior role by that very definition, but how do you communicate that on a Job Posting?\n\nI've seen companies opt for a strategy to look for what they are missing. We do not have anyone who knows \"python + stats + bash + Linux\"? We shall call her ML Engineer.",
"label": "r/datascience",
"dataType": "comment",
"communityName": "r/datascience",
"datetime": "2024-05-22",
"username_encoded": "Z0FBQUFBQm5Lak1PdUpMMVBXaVJZOFJObm02YUFqYVk0cFZmTDVDek43MWpDRF94SkpBeDM3ZFZFcDg0ZDY1TkZPNVJWODYwNVZEMzREV055VGhmOXpwdnNFZk52OUtON1E9PQ==",
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}
Entry Information
- Entry ID: 43395
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000