
Artificial Intelligence Model Developer
2 weeks ago
Machine Learning Engineer
">At a leading tech firm, we are seeking a skilled Machine Learning Specialist to build innovative solutions for clients. As a key member of our team, you will design, develop, and deploy robust machine learning models in a production environment using AWS SageMaker.
Key Responsibilities
- Design and Develop: End-to-end machine learning pipelines on AWS SageMaker to deliver real business value.
- Collaborate with Data Scientists: Translate models and algorithms into production-ready code.
- Manage the ML Lifecycle: Ingest data, train, validate, and deploy models while ensuring model performance and reliability.
- Implement MLOps Best Practices: Automate workflows to optimize model performance, scalability, and cost efficiency on the AWS platform.
- Monitor and Troubleshoot: Deployed models to ensure they meet performance and business requirements.
- Stay Current: The latest advancements in machine learning and cloud technologies.
Required Skills and Qualifications
- Bachelor's or Master's Degree: In Computer Science, Engineering, or a related field.
- Experience: 3+ years in a machine learning or data science role.
- Hands-on Experience: With AWS services, specifically SageMaker, Python, and standard ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Containerization Technologies: Docker.
- MLOps Principles: CI/CD tools.
- Data Engineering Principles: Big data technologies (e.g., Spark, Hadoop).
- Problem-Solving Skills: And collaboration in a fast-paced environment.
Preferred Qualifications
- Experience: Other AWS services such as S3, Lambda, Glue, and Redshift.
- Certifications: AWS Certified Machine Learning – Specialty.
- Model Serving Frameworks: Flask, FastAPI.
- Version Control Systems: Git.
- Agile Development Methodologies:
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