We are seeking an AWS Machine Learning Engineer to develop, deploy, and optimize machine learning models using AWS services. You'll analyze large datasets, build data pipelines, and collaborate with cross-functional teams to deliver data-driven solutions.
Roles and Responsibilities
- Analyze large datasets to extract insights and perform exploratory data analysis (EDA) using AWS tools.
- Build, train, and evaluate ML models using Amazon SageMaker and frameworks like TensorFlow.
- Use AWS Glue, Redshift, and Textract to preprocess and transform data for machine learning.
- Develop end-to-end machine learning pipelines for automated model deployment using AWS services.
- Work with data engineers and business teams to tailor ML solutions to business needs.
- Deploy models to production, monitor performance, and automate model retraining using SageMaker and Lambda.
- Document models, processes, and findings, and communicate results to stakeholders.
Required Skills & Qualifications
- Experience with AWS services (SageMaker, Lambda, Glue, Redshift).
- Proficiency in Python and machine learning libraries (TensorFlow, PyTorch).
- Experience with data preprocessing, ETL, and building ML pipelines.
- Strong collaboration and communication skills.
Preferred Qualifications
- AWS certifications (e.g., AWS Certified Machine Learning – Specialty).
- Experience with deep learning, NLP, or big data tools (Spark, Hadoop).
- Collaborative, fast-paced team with opportunities for continuous learning. Flexible work options available.