Machine Learning Engineer

Machine Learning Engineer (Contract | Remote) Location:Remote (India or LATAM preferred) Contract:6–12 months (extension likely) Start:ASAPOverview We are partnering with a large, enterprise-scale organization that is expanding itsmachine learning and AI capabilitiesas 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 ahands-on Machine Learning Engineerwho 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 usingPython Develop and maintain ML pipelines inAmazon 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 stakeholdersRequired Skills & Experience Strong experience as aMachine Learning Engineeror similar role Hands-on expertise withAmazon SageMaker Strong proficiency inPythonfor ML development Experience deploying models into production environments Ability to work independently in a remote, enterprise setting Strong communication skills and stakeholder-facing experienceNice to Have Experience withGenAI / 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 environmentsWhy 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 environmentHow to Apply Apply with your CV or LinkedIn profile. Shortlisted candidates will be contacted for an initial discussion.

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