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.