Applied AI / ML Engineer

Applied AI / ML Engineer

Experience:

Focus:

Location:

Role Overview

Applied AI / ML Engineer

Key Responsibilities

• Build and integrate

  ML models

  into existing workflows and applications
• Collaborate with

  Data Engineers

  on feature pipelines and data readiness
• Use existing

  ML frameworks and cloud AI services

• Support

  POC, pilot, and production deployments

• Ensure

  explainability, reliability, and performance

  of ML solutions
• Translate

  business problems

  into effective ML approaches

Must-Have Skills

• Strong

  Python

  programming
• Understanding of

  basic ML concepts

  (supervised, unsupervised, evaluation metrics)
• Hands-on experience with at least

  one ML framework

• Ability to convert

  business requirements into ML solutions

Good-to-Have Skills

• Exposure to

  Azure AI services

  or

  OpenAI APIs

• Basic understanding of

  MLOps concepts

• Familiarity with model monitoring and performance tracking

General Expectations (Common Across All Roles)

• Willingness to work in

  shifts

  when required
• Strong

  ownership and accountability mindset

• Continuous learning embedded into day-to-day work

• Cost and efficiency awareness

  in all engineering decisions

• Performance-driven growth mindset

  (no entitlement culture)
• Agreement to

  company terms and conditions

• Work From Office (WFO) – Hyderabad

Best regards,

Nivetha S

Senior Talent Engineer

nivetha.s@eminds.ai