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Senior Machine Learning Engineer

Engineering | Bangalore, India | Full Time

Job Description

About Us:

We are an offer next generation Cognitive Commerce solutions for retailers and brands globally. We work on innovative approaches that connect brands, retailers and consumers. We are looking at going beyond the current trends and hype to create a new standard in Commerce. We have a stellar team plucked from great schools like Stanford, IIT, IIM. This is an opportunity to be associated with a team with a long term vision that also believes in having fun all the way. 

Responsibilities:

  • Work with massively dirty data
  • Develop prototypes, convert to production ready solution in a very quick time
  • Solve complex tasks in text and nlp but with simple Models that train and Infer well
  • Build Data Wrangling, Analysis, Visualization and Modeling solutions on a laptop that deploy and scale with minimal change in code
  • Build model and data pipelines that scale over GPUs and systems on the cloud
  • Experiment with models faster than they can train and use the scientific method to arrive upon a working solution
  • Understand Algorithmic complexity when working with data and ensure all development uses the most optimal solutions
  • Actively participate in research and industry communities including attending conferences, publishing papers

Requirements:

We are looking for really smart, hardcore computer science engineers who can solve complex problems, munch through algorithms and deliver out of the box solutions.  We use neural nets heavily and expect you to be comfortable building NNs.

Ideal candidates must have 2-5 years experience in the following:

  • Required: Master's or PhD (CS, Math, Physics)
  • Required: Experience with  Machine Learning, Neural Networks 
  • Must have publications in leading conferences or Journals
  • Probability and statistics
    • Algorithms/models - Naive Bayes, Gaussian Mixture, Hidden Markov
    •  model evaluation metric - confusion matrices, receiver-operator curves, p-values, etc
  • Applied math and algorithms
    • SVM's
    • gradient decent, convex optimization, lagrange, quadratic programming, partial differential equations and alike
  • Python/C++/R/Java 
  • Distributed computing
  • Expertise in unix tools
  • Advanced signal processing techniques

Perks:

  • Options
  • Create your own schedule