About the team● The machine learning team is a self-contained team of 9 people responsible for building models and services that support key workflows for IDfy.● Our models are gating criteria for these workflows and as such are expected to perform accurately and quickly. We use a mix of conventional and hand-crafted deep learning models.● The team comes from diverse backgrounds and experiences. We have ex-bankers, startup founders, IIT-ians, and more.● We work directly with business and product teams to craft solutions for our customers. We know that we are, and function as a platform and not a services company.● Be working on all aspects of a production machine learning system. You will be acquiring data, training and building models, deploying models, building API services for exposing these models, maintaining them in production, and more.● Work on performance tuning of models● From time to time work on support and debugging of these production systems● Work on researching the latest technology in the areas of our interest and applying it to build newer products and enhancement of the existing platform.● Building workflows for training and production systems● Contribute to documentationAbout you● You are an early-career machine learning engineer (or data scientist). Our ideal candidate issomeone with 1-3 years of experience in data science.Must Haves● You have a good understanding of Python and Scikit-learn, Tensorflow, or Pytorch. Our systems are built with these tools/language and we expect a strong base in these.● You are proficient at exploratory analysis and know which model to use in most scenarios● You should have worked on framing and solving problems with the application of machine learning or deep learning models.● You have some experience in building and delivering complete or part AI solutions● You appreciate that the role of the Machine Learning engineer is not only modeling, but also building product solutions and you strive towards this.● Enthusiasm and drive to learn and assimilate the state of art research. A lot of what we are building will require innovative approaches using newly researched models and applications.Good to Have● Knowledge of and experience in computer vision. While a large part of our work revolves around computervision, we believe this is something you can learn on the job.● We build our own services, hence we would want you to have some knowledge of writing APIs.● Our stack also includes languages like Ruby, Go, and Elixir. We would love it if you know any of these or take an interest in functional programming.● Knowledge of and experience in ML Ops and tooling would be a welcome addition. We use Docker and Kubernetes for deploying our services.
1. The candidate should be passionate about machine learning and deep learning.2. Should understand the importance and know-how of taking the machine-learning-based solution to the consumer.3. Hands-on experience with statistical, machine-learning tools and techniques4. Good exposure to Deep learning libraries like Tensorflow, PyTorch.5. Experience in implementing Deep Learning techniques, Computer Vision and NLP. The candidate should be able to develop the solution from scratch with Github codes exposed.6. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library.7. Should be strong in data structures and algorithms. Should be able to do code complexity analysis/optimization for smooth delivery to production.8. Expert level coding experience in Python.9. Technologies: Backend - Python (Programming Language)10. Should have the ability to think long term solutions, modularity, and reusability of the components.11. Should be able to work in a collaborative way. Should be open to learning from peers as well as constantly bring new ideas to the table.12. Self-driven missile. Open to peer criticism, feedback and should be able to take it positively. Ready to be held accountable for the responsibilities undertaken.