NTRO Recruitment 2022: National Technical Research Organization (NTRO) has announced the announcement of IT Professionals/ Engineers. Those Interested in this notification and with all the required qualifications can go through the Notification thoroughly and then apply online.
| Name of the Post: | NTRO IT Professionals/ Engineers |
| Post Date: | 21-10-2022 |
| Total Vacancy: | 125 |
NTRO registration of desirous lT Professionals for engagement as Consultant in the following positions purely on a contract basis, for which the ONLINE registration is scheduled to begin on October 19th (Wednesday) (1700 Hrs) and will close on 07.11.2022 (Monday) (1700 Hrs).
National Technical Research Organization
NTRO Recruitment 2022
New Delhi/Bengaluru/Mumbai/Kolkata
125 vacancy
IT Professionals/ Engineers
Age Limit
| Μίnimum Age | 18 years |
| Maxίmum Age | 62 Years * |
Age Relaxation application as per the Rule.
Application Fee
- General Candidates: NA
- OBC-A&B Candidates: NA
- SC/ ST & PH: NA
- Payment Mode: NA
Important Dates
| Starting Date to Apply Online | 19-10-2022 |
| Closing Date to Apply Online | 07-11-2022 |
Qualification
- Candidate Should Possess BE/ B.Tech/ M.Tech/ MCA (Relevant)
Vacancy Details
| No | Name of the Post | No of Vacancy |
|---|---|---|
| 1 | IT Professionals/ Engineers | 125 |
Kindly read the full Notification Before Apply Online.
Important Links
| Apply Online | Click Here |
| Download Official Notification | Click Here |
| Official Website | Click Here |
About NTRO Recruitment 2022: National Technical Research Organization
The evaluation/ selection criteria are grounded on the Quality & Cost Grounded Selection Method'( ecBS) of choice in the rate of 8020( 80 weightage to quality( qualification, skill set, experience, industry certification, performance n interview, etc.) and 20 weightage to cost( anticipated salary).
( i) originally, develop and apply the right algorithms and models and tools for textbook, image videotape and Audio analysis
( ii) Train, test, and emplace models locally as well as in a private pall.
(iii) Secondly, preprocessing and storehouse of data for training and testing the AI/ ML models
( iv) Thirdly, maintaining all models along with the development and updating of law and process attestation.
( v) still, vindicating data quality and/ or icing data cleanliness
( vi) Chancing available datasets in open source data that could be used for training
(vii) Specifying the preprocessing or point engineering that will be performed on a given dataset.
(viii) augmentalon ppelnes data description
(ix) assaying model crimes and contriving strategies to overcome them
( x) Eventually, model deployment to the product