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ML Engineer 3 applications

Job Overview

  • Postal Code NA
  • Salary Offers 6 months’ internship with 8k to 20 K Stipend
  • Experience Level Junior
  • Total Years Experience 0-5
  • Qualification Required Post Graduation
  • Education Details Master's (Preferred) Computer Application

Job opening for ML Engineers in an AI startup. Looking for candidates with knowledge in python, machine learning, keras etc.

Job Description

Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress

Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability

Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world

Verifying data quality and/or ensuring it via data cleaning

Finding available datasets online that could be used for training

Defining validation strategies

Defining the pre-processing or feature engineering to be done on a given datasets

Defining data augmentation pipelines

Training models and tuning their hyper parameters

Analyzing the errors of the model and designing strategies to overcome them

Deploying models to production

Job Requirements

Proficiency with Python

Knowledge of TensorFlow, PyTorch, CNN, R-CNN, YOLO, Caffe, Similar Machine Learning Deep Leaning Platforms

Excellent skills developing in C/C++ or Python as well as significant experience working in a Linux environment

Hands-on experience with data science tool kits like: R, Pandas, Jupyter, Scikit, TensorFlow, etc.

Exposure to state-of-the-art techniques in ML and NLP

Understanding of data structures, data modelling and software architecture

Outstanding analytical and problem-solving skills

Expertise in visualizing and manipulating big datasets

Proficiency with OpenCV, CUDA

Proficiency with Linux and Windows CLI

Ability to make quick decisions in high-pressure environments with limited information.

 

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