Job Summary:In this role, you will design and implement algorithmic product architectures to operationalize machine learning models across the entire product lifecycle" from data ingestion to ML processing and result delivery. As both a solution architect and hands-on engineer, you will collaborate with data science, data engineering, and architecture teams to ensure scalable, efficient, and secure ML product deployments in cloud environments.
Job Responsibilities:- Design workflows and architectures that activate ML models, including real-time streaming and batch processing use-cases.
- Collaborate with data scientists to develop and prototype algorithmic product solutions using appropriate AWS services.
- Implement production-ready solutions using infrastructure-as-code (Terraform/CloudFormation).
- Develop data pipelines to populate and maintain a feature store with cleaned and imputed data.
- Enhance and scale existing ML product architectures to maximize business impact.
- Partner with data engineering to align on data formatting, delivery cadence, and integration.
- Ensure all ML solutions adhere to data governance, security, and architectural standards.
- Continuously stay updated on new AWS ML services, tools, and design patterns.
Required Skills:- Strong experience building ML systems in cloud environments (especially AWS).
- Expertise in ML frameworks like PyTorch and TensorFlow, including distributed training and model optimization.
- Hands-on experience with cloud tools and infrastructure: EC2, EKS, S3, SageMaker, Docker, Kubernetes, Terraform/CloudFormation.
- Proficient in Python and big data tools such as Apache Spark and Databricks.
- Solid understanding of LLM fine-tuning, transformer models, and model deployment strategies.
Preferred Skills:- Familiarity with MLOps and CI/CD for ML workflows.
- Experience in feature engineering and maintaining enterprise-grade feature stores.
- Understanding of data governance and security practices in cloud-based environments.
Certifications:[Optional AWS certifications or relevant ML engineering certifications preferred.]
Education:Master's degree in computer science, Software Engineering, Machine Learning, or a related field.
