Python/AWS Software Engineer (REMOTE- No C2C/H1B)
No C2C/H1B
Please note that this is a 6-month contract position with the possibility to extend.
This role is Remote - Must be able to support EST.
Experience & Considerations
3-5 years of experience.
Certifications (e.g., AWS, Python) are a plus, but hands-on experience with Python is more important.
Key Responsibilities
Develop and implement new features with initial problem-solving guidance.
Work within an existing mid-size codebase using Python, Git, and AWS.
Collaborate with senior engineers for solutioning and debugging.
Write clean, maintainable, and scalable code with a focus on software development (OOP) rather than data analytics.
Support the engineering team by contributing to coding efforts but not involved in CI/CD development.
Required Qualifications
Strong proficiency in Python (OOP and software development experience).
Experience with Git/GitHub and version control workflows.
Comfortable working with AWS (a plus, but not required).
Exposure to data science or ML models is beneficial but not a must-have.
Special Skill Requirements:
Strong Coding experience.
Python
Object Oriented Programing
AWS SageMaker
Git, GitHub
Additional Qualification:
Demonstrated analytical skills.
Demonstrated problem solving skills.
Possesses strong technical aptitude.
Experience with: Experience designing and building scalable enterprise ML Ops frameworks and pipelines including integration, testing, deployment, monitoring, infrastructure management, audit and governance.
Advanced understanding and practical application of workflow orchestration processes and technologies.
Ability to simultaneously handle multiple priorities.
Seeks to acquire knowledge in area of specialty.
Highly thorough and dependable.
Effectively coaches and delivers constructive feedback.
Education Requirements:
High School Diploma or equivalent required.
Bachelor's degree preferred.
Competencies:
Python
Object Oriented Programing
AWS SageMaker
Git, GitHub
Additional Qualification:
Demonstrated analytical skills.
Demonstrated problem solving skills.
Possesses strong technical aptitude.
Experience with: building and maintaining end-to-end machine learning pipelines in production environments.
Experience with model and data versioning, model deployment, model serving and monitoring.
Intermediate knowledge of workflow orchestration processes and technologies.
Ability to simultaneously handle multiple priorities.
Seeks to acquire knowledge in area of specialty.
Essential Job Functions:
- Utilizes complex knowledge of machine learning engineering concepts and principles to apply skills in a business environment.
- Primarily focused on productionizing machine learning models and systems at scale.
- Performs work independently or with minimal guidance, depending on task complexity.
- May function as technical lead on assigned projects.
- Delivers specific ML Ops engineering tasks such as moderate to complex level designing, developing, implementing, optimizing, and maintaining models, systems, and applications using existing and emerging technology platforms.
- Collaborates with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions.
- Projects are generally of moderate complexity. Consults on the design, development, and implementation of DevOps and ML Ops pipelines.
- May lead portions of deployment processes under guidance from people leader.
- Reviews, verifies, validates, and troubleshoots code to ensure high availability and high performance of machine learning models and applications. Uses complex knowledge and understanding of code management principles and best practices to follow architectural and governance guidelines.
- Effectively communicates and applies machine learning engineering value, concepts, and strategies across multiple scenarios.
Applicants must provide their phone number. Reference job number A4567.
No C2C/H1B
Please note that this is a 6-month contract position with the possibility to extend.
This role is Remote - Must be able to support EST.
Experience & Considerations
3-5 years of experience.
Certifications (e.g., AWS, Python) are a plus, but hands-on experience with Python is more important.
Key Responsibilities
Develop and implement new features with initial problem-solving guidance.
Work within an existing mid-size codebase using Python, Git, and AWS.
Collaborate with senior engineers for solutioning and debugging.
Write clean, maintainable, and scalable code with a focus on software development (OOP) rather than data analytics.
Support the engineering team by contributing to coding efforts but not involved in CI/CD development.
Required Qualifications
Strong proficiency in Python (OOP and software development experience).
Experience with Git/GitHub and version control workflows.
Comfortable working with AWS (a plus, but not required).
Exposure to data science or ML models is beneficial but not a must-have.
Special Skill Requirements:
Strong Coding experience.
Python
Object Oriented Programing
AWS SageMaker
Git, GitHub
Additional Qualification:
Demonstrated analytical skills.
Demonstrated problem solving skills.
Possesses strong technical aptitude.
Experience with: Experience designing and building scalable enterprise ML Ops frameworks and pipelines including integration, testing, deployment, monitoring, infrastructure management, audit and governance.
Advanced understanding and practical application of workflow orchestration processes and technologies.
Ability to simultaneously handle multiple priorities.
Seeks to acquire knowledge in area of specialty.
Highly thorough and dependable.
Effectively coaches and delivers constructive feedback.
Education Requirements:
High School Diploma or equivalent required.
Bachelor's degree preferred.
Competencies:
Python
Object Oriented Programing
AWS SageMaker
Git, GitHub
Additional Qualification:
Demonstrated analytical skills.
Demonstrated problem solving skills.
Possesses strong technical aptitude.
Experience with: building and maintaining end-to-end machine learning pipelines in production environments.
Experience with model and data versioning, model deployment, model serving and monitoring.
Intermediate knowledge of workflow orchestration processes and technologies.
Ability to simultaneously handle multiple priorities.
Seeks to acquire knowledge in area of specialty.
Essential Job Functions:
- Utilizes complex knowledge of machine learning engineering concepts and principles to apply skills in a business environment.
- Primarily focused on productionizing machine learning models and systems at scale.
- Performs work independently or with minimal guidance, depending on task complexity.
- May function as technical lead on assigned projects.
- Delivers specific ML Ops engineering tasks such as moderate to complex level designing, developing, implementing, optimizing, and maintaining models, systems, and applications using existing and emerging technology platforms.
- Collaborates with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions.
- Projects are generally of moderate complexity. Consults on the design, development, and implementation of DevOps and ML Ops pipelines.
- May lead portions of deployment processes under guidance from people leader.
- Reviews, verifies, validates, and troubleshoots code to ensure high availability and high performance of machine learning models and applications. Uses complex knowledge and understanding of code management principles and best practices to follow architectural and governance guidelines.
- Effectively communicates and applies machine learning engineering value, concepts, and strategies across multiple scenarios.
Applicants must provide their phone number. Reference job number A4567.