Machine Learning Engineer mytat.co

About Mytat.co

MYTAT is an integrated HR Solution Platform & Edtech Solution as PaaS (Platform as A Service) MYTAT enables HR Functions with Applicant Tracking System (ATS), Assessments, Lateral and Campus Hiring Solutions, and Learning Management System (LMS). Being AICTE's NEAT partner, MYTAT has reached in educational institutions across India. Powered by AI/ML technology-based engine, it has its own proprietary audio and video communication channel. Therefore, whether it is MCQ, Aptitude, Psychometric, Coding, Subjective or Psychometric assessment, MYTAT helps you with GDPR compliant standards in Managing Talent Intake and Talent Transformation. On the other hand, it provides a complete eco-system for Educational Intuitions.

Job Description

Location: Pan India (WFH) but candidate needs to be comfortable with travelling to Hyderabad job location if need be.
Budget- 4+ years 20 LPA (max), 7+ years and the candidate is good then 35 LPA (max)
Notice Period- Immediate to 30 days (max). If candidate is ready to join early then joining bonus can also be provided.
Total Experience- 4+ years
Relevant Experience- minimum 4 years is required. 
Education required- Computer Science or Computer Engineering.
No. of positions- 5
Skills required- Image and video processing, Machine Learning, Python, Python web framework, e.g. Flask, Django or FastAPI, PyTorch,TensorFlow, GPU-based training infrastructures, Docker, Pyspark or Tableau, RDBMS and NoSQL Database.  
Interview Process: R1- Technical round, R2- Coding Assessment, R3- discussion with CTO, R4- discussion with CEO (if need be). 

Sr. Computer Vision/ML Engineer:

Visionify is working on bringing the power of Computer Vision and AI to everyday use cases. We are Sr. Computer Vision/ML Engineer.
Visionify is working on bringing the power of Computer Vision and AI to everyday use cases. We are looking to hire a strong, motivated, and enthusiastic Machine Learning Engineer to execute.
our roadmap. We are looking for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.

Responsibilities:

- Understanding business objectives and developing software and models that help achieve them. The software could involve a training framework, - -inference framework, working with different technologies for ML.
- 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
- Develop processes for different common operations of the team: data acquisition, model training, and prototype development.
- Feature Engineering and Data Modeling.
- Transforming data science prototypes and applying appropriate ML algorithms and tools.
- Finding open-source datasets for prototype development.
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Data Visualization Tool Experience Pyspark, Tableau, etc.
- Training models and tuning their hyperparameters.

Requirements:

- Bachelors/Masters's degree in Computer Science/Computer Engineering/IT or related fields.
- 5+ years of experience. Exceptional candidates with less experience are welcome to apply.
- Industry experience working regression Model (Tensorflow, Keras, Model Training/Inference, etc).
- Strong experience with RDBMS and NoSQL databases and different datasets like Excel, CSV, JSON, etc...
- Strong experience with Python, R, and writing reusable code.
- Strong experience working with regression models and classification models.
- Experience working with pandas, Numpy, and Scikit packages and python visualization packages.
- Experience with Python web framework, e.g. Flask, Django or FastAPI
- Experience with different ML platforms: PyTorch,TensorFlow.
- Experience with utilizing various GPU-based training infrastructures.
- Experience with Docker
- Experience with Pyspark or Tableau.