ML Engineer

Location: India, US, Canada (Vancouver/Toronto)

Job description:

We are on the constant lookout for Machine Learning Engineers who are interested in developing cutting-edge technologies for real-world next-generation AI-driven insights platforms. The ideal candidate will be equally comfortable with theoretical thinking, coding and academic writing.

Responsibilities:

  • Implementing highly scalable Natural Language Processing (NLP) and Data Science services capable of processing extremely large volumes of data.
  • Contributing to the design of highly available, highly scalable, machine learning workflows.
  • Create and implement non-standard, fresh and creative scientific ideas to improve or speed up existing technologies.
  • Collaborate with product managers and dive deeper into the usage of the research, brainstorm with the product team on developing new creative ideas.
  • Follow up and support the development of models in an end-to-end manner: from design to production.
  • Analyze, interpret and explain outcomes of non-trivial experiments.
  • Analyze the data used in experiments, understand its subtleties of it, and modify it appropriately, if needed.

Requirements and skills:

  • Strong working knowledge (at least 2 years) of Java or Python.
  • Strong working knowledge (at least 2 years) of machine learning frameworks, in particular, TensorFlow and Keras.
  • Working knowledge of Java or Python.
  • Working knowledge of machine learning frameworks, in particular, TensorFlow and Keras.
  • Good knowledge of data analysis and machine learning, in particular around Natural Language Processing.
  • Familiarity with infrastructure as code (e.g., Terraform, Cloud formation, Serverless), continuous integration and deployment.
  • Good knowledge of Unix/Linux systems and bash/shell scripting.

Required Qualifications:

  • UG: B.Tech/B.E. in any specialization
  • PG: Any Postgraduate

NB: Flexday promotes a flexible work model supporting a blend of in-office, remote, and on-the-go work styles as per employee convenience.