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Applied ML Engineer

Min Experience

5 years

Location

India

JobType

full-time

About the job

Info This job is sourced from a job board

About the role

A bit about the Founder: Thejo, is a multiple-time founder who previously built Airbase (acquired by Paylocity for ~$400M) and Automatic (YC S11, acquired by SiriusXM for $115M). He has since started his own venture studio, where he is incubating a couple of companies and building the initial teams.

About The Role

We are looking for an Applied ML Engineer! We are building next-generation AI-native products, and seeking talented engineers passionate about machine learning and making an impact at an early-stage company.

Responsibilities

  • Ship and support AI-native products from concept to production.
  • Apply sound judgment on building and maintaining high-performing production ML systems.
  • Stay deeply informed on the latest machine learning research and developments.
  • Collaborate with a team of strong engineers; serve as a mentor and resource for other high-potential ML engineers.

Skills & Experience Needed

  • 5+ years of experience in delivering and supporting production AI/ML products.
  • Have an advanced degree in machine learning, theoretical computer science, mathematics, or physics.
  • Excellent decision-making skills regarding large-scale ML system design and maintenance.
  • Strong awareness of current trends and progress in machine learning research.
  • A drive to want to work with and learn from, eager to help shape a high-caliber engineering team.
  • A proven track record with companies known for strong engineering cultures, including meaningful startup experience.

About the company

Thejo, is a multiple-time founder who previously built Airbase (acquired by Paylocity for ~$400M) and Automatic (YC S11, acquired by SiriusXM for $115M). He has since started his own venture studio, where he is incubating a couple of companies and building the initial teams.

Skills

machine learning
ml
ai
large-scale ml system design
production ml systems