Job description
Role overview
Support the development and industrialization of data-driven products and machine learning solutions for supply chain optimization. Lead end-to-end ML project lifecycle from proof-of-concept to minimum viable product deployment using cloud-native architectures.
Collaborate with cross-functional teams to implement scalable machine learning pipelines on AWS infrastructure. Focus on operationalizing AI models while maintaining high standards of data governance and system reliability.
Responsibilities
- Design and implement machine learning solutions for supply chain challenges
- Operationalize ML models through cloud-based CI/CD pipelines
- Collaborate with data scientists to translate research into production-ready systems
- Monitor and optimize ML model performance in production environments
Requirements
- 4+ years of ML engineering experience with AWS ecosystem
- Proven expertise in MLOps practices and model deployment
- Strong Python programming skills with ML frameworks (TensorFlow/PyTorch)
- Experience with cloud infrastructure (AWS Lambda, EC2, S3) and containerization
Benefits
- Flexible freelance engagement with competitive daily rates
- Work on cutting-edge AI applications for enterprise clients
Keywords
AWSMLOpsPythonMachine LearningCloud EngineeringData PipelineSupply Chain OptimizationML Model DeploymentDevOpsJenkins