Junior GenAI-ML Engineer
Junior GenAI-ML Engineer
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Job Description
Seeking a motivated and enthusiastic Junior Machine Learning Engineer who can work with CR (Corporate Research) and develop high quality AI solutions for our advanced engineering team. The ideal candidate will have a foundational understanding of time series concepts process curve usecases and experience with relevant tools and technologies. As a ML Engineer you will work alongside senior engineers and researchers to develop and implement ML algorithms and solutions for a variety of applications on time series and tabular data.
Roles & Responsibilities:
Algorithm Development: Assist in designing and implementing machine learning algorithms for tasks such as regression classification clustering and deep learning.
Data Processing: Contribute to preprocessing and augmenting image datasets to ensure highquality input for model training and evaluation.
Model Training: Support the training and evaluation of ml models including Optimize models for accuracy performance and scalability and assessing performance metrics.
Software Development: Hands on experience with the software development to integrate AI solutions into existing applications and systems.
Model Deployment: Deploy and monitor machine learning models in production environments. Implement CI/CD pipelines for model integration and updates
Testing and Debugging: Participate in testing and debugging processes to ensure the robustness and accuracy of ensembled algorithms and solutions.
Documentation: Maintain clear and comprehensive documentation of algorithms experiments and code to facilitate knowledge sharing and reproducibility.
Collaboration: Work closely with other engineers researchers and stakeholders to understand project requirements and deliver effective solutions.
Required skills:
Technical Skillset
- Strong understanding of
Linear Algebra
Multiverse Calculus
Probability and stochastic processes
Optimization methods
Feature Engineering
Comprehensive knowledge on
Gradient Boosted Trees
Explainable Boosted Machines
KNC
KNN
Hands On Experience in
Scikit Learn
tsfresh
xgboost
pandas
lighgbm
NumPy
MLOps frameworks like mlflow
Familiarity with databases (SQL and NoSQL)
Understanding of widely used ML techniques and machine learning algorithms.
Proficiency in programming languages in python knowledge in C or Java are advantage.
ProblemSolving: Strong analytical and problemsolving skills with the ability to work independently and as part of a team.
Communication: Good communication skills with the ability to convey technical concepts clearly to both technical and nontechnical stakeholders.
Attention to Detail: High attention to detail and commitment to delivering highquality work.
Qualifications :
B.E./MS/B. Tech. in Electronic or Computer Science
Additional Information :
34 years experience
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
