aimlroles

Machine Learning Engineer

Aidaptive aidaptive.com Open · verified Oct 22, 2026
Remote India Full-time Mid-level Machine Learning Engineering

At a glance

Mid-level Machine Learning Engineering role at Aidaptive. Remote, India · full-time.

Pay not stated Machine Learning Engineer salary

RoleMachine Learning Engineering
SeniorityMid-level
LocationIndia
WorkplaceRemote
EmploymentFull-time
PostedApr 4, 2022 · 4y ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build ML approaches for practical problems at large scale
  • Create, test, maintain and refine machine learning models
  • Balance project priorities, deadlines and deliverables

What you bring

  • A computer science or mathematics degree, or comparable hands-on experience
  • Python experience for modeling, plus work with TensorFlow and other machine learning libraries

Who this fits

This mid-level role suits an engineer focused on developing and improving machine learning models. It is remote in India.

From the employer

  • Machine Learning Engineer

Role:

We're a global team with a track record of building world class enterprise products and are seeking talented Machine Learning Engineers to develop and optimize ML models.

Minimum qualifications:

  • Bachelor's degree in Computer Science, Mathematics, or equivalent practical experience.
  • Python development experience for modeling.
  • Experience with deep learning frameworks including TensorFlow and other machine learning libraries

Preferred qualifications:

  • Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
  • Experience in building, deploying, and improving machine learning models and algorithms in real-world products.
  • Experience with one or more of the following: natural language processing, computer vision, recommendation systems or similar.

Responsibilities:

  • Develop solutions for real world, large scale problems.
  • Design, develop, test, maintain and improve Machine Learning models.
  • Manage project priorities, deadlines, and deliverables.