As an AI Engineer, at Widas Concepts India Pvt. Ltd. you will be part of a team that is analysing problems that can be resolved using Machine Learning. You will evaluate what techniques would be appropripriate, benchmark, keep track of best practices and help configure and work with our AI production infrastructure. To succeed you must become proficient with Machine Learning concepts, techniques and tools and have clear understanding of dependencies while moving them to production.
- Analyze requirements and understand how to apply machine learning concepts for the problem on hand.
- Background in Data Science would be a plus.
- Be able to evaluate multiple models and tools, benchmark and come with recommendations
- Must be familiar to ingest data carry out necessary transforms.
- Be able to transfer your proof of concepts to production environments and configure for real time systems in our Big Data /Java framework.
- Be able to fine tune for production scales.
- Familiarity with Botnet Detection & Fraud Detections in cloud frameworks would be a plus.
- Understanding of hardware and computing complexities and familiarity with some CUDA , GPU etc a plus.
- Identify and transfer learning opportunities and new training datasets.
- Build AI models from scratch and demonstrate performance and impact.
- Quick learner and have adapting capabilities to wade through full technology stack of a cloud / micro services architecture.
- Keep up to date with the latest AI research relevant to our business domain.
Skills & Experience
- At least 3 years hands-on programming experience working on machine learning models.
- Demonstrated proficiency in multiple programming languages with a strong foundation in any tools such as Python, R.
- Experience using neural net libraries like Keras on deep learning platforms like TensorFlow, Torch, Pytorch or Theano and optimizations on such.
- Familiarity or working experience with large-scale distributed deep learning on Hadoop, data streams using Spark on CPU, GPU local or cloud.
- Familiarity or work experience with CNN , RNN, anomaly detection, autoencoders in fraud detection.
- Image grading techniques using deep learning models for medical image processing.
What can you expect?
- You would be evaluating and deciding the best ML techniques and tools for a given challenge.
- Deploying and training models to build autonomous disease detection systems.
- You will be identifying techniques anomaly and fraud detection systems for a security and identity product.
- You would be taking existing models and best practices and adept them to our environment and business problems.
- You will also be required to deploy software into production by building maintainable, readable, modular solutions using modern software engineering best practices.
- Be ready to talk about your experiences doing code reviews, building interfaces, and deployment systems.
- You would be working with our enthusiastic, bright and pragmatic product team.
|Job Category||System Engineering|