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.
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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