AI - ML Engineer
KeySkills
Company Name
Job Description
- Job description
- Must have experience with Machine Learning Model Development
- Expert Level Proficiency in Data Handling (SQL)
- Hands-on with Model Engineering and Improvement
- Strong experience in Model Deployment and Productionlization
- Extensive experience in developing and implementing machine learning, Deep Learning, NLP models across various domains,
- Strong proficiency in Python, including relevant libraries and frameworks for machine learning, such as scikit-learn, XGBoost and Keras. Ability to write efficient, clean, and scalable code for model development and evaluation.
- Proven experience in enhancing model accuracy through engineering techniques, such as feature engineering, feature selection, and data augmentation. Ability to analyze model samples in relation to model scores, identify patterns, and iteratively refine models for improved performance.
- Strong expertise in deploying machine learning models to production systems. Familiarity with the end-to-end process of model deployment, including data preprocessing, model training, optimization, and integration into production environments.
Job Details
Experience :
0 To 1
Number Of
Vacancies :
20
Job Type :
Permanent
Industry Type : IT/Software
Salary
:
5 Lac - 12 Lac++
P.A
Education Summary
UG :
Any UG Degree
PG :
Any PG Degree
Contact Details
Contact
Person :
NA
Contact
Number :
8041042084
e-mailId :
vijayanath.siddhareddy@capgemini.com
Address :
Capgemini Technology Services India Limited,
Eco Space, Pritech Park SEZ,Building 6B, Village, Bellandur,
Outer Ring Road, Bellandur, Bangalore.
Office Location
Central Jakarta No 1234, Jakarta, IndonesiaAzure.Net - AI
Experience -
0 to 1
FULL STACK DEVELOPER
Experience -
5 to 8
AI - ML Engineer
Experience -
0 to 1
Software Development Engineer
Experience -
0 to 5
Key Skills -
Java,
Python,
C++,
JavaScript,
Object-Oriented Programming,
Data Structures and Algorithms,
HTML,
CSS,
Backend development,
Spring Boot,
Node.js,
REST APIs,
Microservices,
MySQL,
PostgreSQL,
MongoDB,
SQL,
Git,
GitHub,
Unit testing,
Debugging,
Agile methodology,
CI/CD,
Docker,
Kubernetes,
Cloud platforms (AWS,
Azure,
GCP),