Machine Learning Engineer

Machine Learning Engineer (Contract | Remote) Location:

Remote (India or LATAM preferred) Contract:

6–12 months (extension likely) Start:

ASAP

Overview We are partnering with a large, enterprise-scale organization that is expanding its

machine learning and AI capabilities

as part of a broader data and digital transformation. The team is focused on building scalable, production-grade ML solutions that directly support business operations and decision-making.

We are seeking a

hands-on Machine Learning Engineer

who is comfortable working across the full ML lifecycle from model development to deployment and optimization in a cloud environment.

Key Responsibilities Design, build, train, and deploy machine learning models using

Python Develop and maintain ML pipelines in

Amazon SageMaker

(training, tuning, deployment, monitoring) Collaborate closely with data engineers, analytics teams, and business stakeholders to translate requirements into ML solutions Support model experimentation, evaluation, and iteration to improve accuracy and performance Implement best practices for model versioning, monitoring, and performance tracking Contribute to GenAI and advanced analytics initiatives where applicable Clearly communicate technical concepts, model outputs, and recommendations to non-technical stakeholders

Required Skills & Experience Strong experience as a

Machine Learning Engineer

or similar role Hands-on expertise with

Amazon SageMaker Strong proficiency in

Python

for ML development Experience deploying models into production environments Ability to work independently in a remote, enterprise setting Strong communication skills and stakeholder-facing experience

Nice to Have Experience with

GenAI / LLM-based solutions Familiarity with MLOps concepts (model monitoring, drift detection, retraining) Experience integrating ML models with data pipelines or APIs Prior experience in large-scale or regulated enterprise environments

Why Apply Long-term contract with strong extension potential Opportunity to work on real, production ML systems Exposure to AI, ML, and GenAI initiatives at enterprise scale Fully remote role with flexible working environment

How to Apply Apply with your CV or LinkedIn profile. Shortlisted candidates will be contacted for an initial discussion.