We are seeking a hands-on Machine Learning Engineer to design, build, train, and deploy machine learning models using Python. The ideal candidate will have strong experience in Amazon SageMaker and Python for ML development, with the ability to work independently in a remote, enterprise setting.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
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.
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