I am an L4 MLE with 7 years of work ex. My work is boring as hell and there is barely any ML. I want to move into a research scientist role.
My original plan was to stay at google for another year and apply for a PhD. But I am thinking switching to either Amazon or Microsoft would be a better idea. I have a couple of question:
1. Is your pre PhD experience not counted afterwards? Would I have to join as an L4 again?
2. How likely is it for me to get into a research org internally? I have research experience and would have a couple of publications in the next 6 months through external collaboration
Blind tax
TC: 70 LPA
Want to see the real deal?
More inside scoop? View in App
More inside scoop? View in App
blind
SUPPORT
FOLLOW US
DOWNLOAD THE APP:
FOLLOWING
Industries
Job Groups
- Software Engineering
- Product Management
- Information Technology
- Data Science & Analytics
- Management Consulting
- Hardware Engineering
- Design
- Sales
- Security
- Investment Banking & Sell Side
- Marketing
- Private Equity & Buy Side
- Corporate Finance
- Supply Chain
- Business Development
- Human Resources
- Operations
- Legal
- Admin
- Customer Service
- Communications
Return to Office
Work From Home
COVID-19
Layoffs
Investments & Money
Work Visa
Housing
Referrals
Job Openings
Startups
Office Life
Mental Health
HR Issues
Blockchain & Crypto
Fitness & Nutrition
Travel
Health Care & Insurance
Tax
Hobbies & Entertainment
Working Parents
Food & Dining
IPO
Side Jobs
Show more
SUPPORT
FOLLOW US
DOWNLOAD THE APP:
comments
Is SWE ML role in Google India not good ?
Can you give some idea about the team and product you are working on?
Why do you feel it’s boring? Any particular pain points?
The scope is also very limited due to too much middle management. You have to fight a lot for projects.
I have been forced into backend work multiple times.
Can’t tell you about the projects but they are except that ML work has been mainly force fitting models.
I used to work on real ML models in my earlier role. There is barely any ML work in my team. And from what I have heard from other ML engineers it just involves making a lot of data pipelines and tfx services with predicting models.