Machine Learning Engineer (Contract | Remote)
Location: Remote (India or LATAM preferred)
Contract: 612 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.
