Resource Informatics Group

Job Title: Sr Python Full Stack Developer (Locals Only). Design and implement frameworks and tools to streamline the machine learning process. Leverage software architecture and design patterns to develop fault tolerant microservices. Experience with common Python Data Engineering packages including Pandas, Numpy, Pyarrow, Pytest, Scikit-Learn, and Boto3. Knowledgeable of Client platform technologies including Apache Airflow, Kubernetes, Dask, Ray, and MLFlow

full stack developer

Job Title: Sr Python Full Stack Developer (Locals Only)
Location: Houston, Texas
Duration: 6+ months
Responsibilities include:
• Work directly with Business domain experts and Data Scientists to develop high quality, reliable, scalable, machine learning systems
• Design and implement frameworks and tools to streamline the machine learning process
• utomate manual data collection and processing tasks to improve efficiency
• Leverage software architecture and design patterns to develop fault tolerant microservices
• Convert research-based machine learning models into production-ready software
• Implement processes to ensure coding standards, code quality, documentation, and test coverage<br/><br/>The successful candidate will meet the following qualifications:
• 10+ years in IT and 7+ years of programming experience in Python
• Expertise in developing and maintaining data pipelines
• Experience in testing, packaging, and deploying machine learning models
• Experience in software engineering practices such as Design Principles and Patterns, Unit Testing, Refactoring, CI/CD, and version control
• Expertise in Object-Oriented Design Principals and Functional Programming Principals
• Experience with common Python Data Engineering packages including Pandas, Numpy, Pyarrow, Pytest, Scikit-Learn, and Boto3
• Experience in storage technologies including SQL relational databases and Object Storage such as AWS S3
• Experience in implementing distributed computing systems
• Experience in designing modular, reusable software components
• Experience in developing API endpoints and microservices
• Knowledgeable of MLOps Principles
• Knowledgeable of Client platform technologies including Apache Airflow, Kubernetes, Dask, Ray, and MLFlow

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