Senior Infrastructure Engineer

Summary

Join DT Professional Services as a Senior Infrastructure Engineer and leverage your expertise in machine learning engineering to productionize models and systems at scale. You will collaborate with cross-functional teams, design and implement ML Ops pipelines, and ensure high performance of machine learning applications. This remote position requires strong coding skills (Python, AWS SageMaker, Git), experience with ML Ops frameworks, and the ability to handle multiple priorities. The role may involve leading portions of deployment processes and providing technical leadership on projects. This position offers competitive compensation and a comprehensive benefits package.

Requirements

• Have a High School diploma or equivalent
• Have 3-5 years of related experience
• Possess strong coding experience in Python, Object Oriented Programming, AWS – SageMaker, Git and Github
• Have experience designing and building scalable enterprise ML Ops frameworks and pipelines including integration, testing, deployment, monitoring, infrastructure management, audit and governance
• Have experience with building and maintaining end-to-end machine learning pipelines in production environments
• Have experience with model and data versioning, model deployment, model serving and monitoring
• Have intermediate knowledge of workflow orchestration processes and technologies
• Be able to simultaneously handle multiple priorities
• Demonstrate analytical skills
• Demonstrate problem solving skills
• Possess strong technical aptitude
• Have advanced understanding and practical application of workflow orchestration processes and technologies
• Seek to acquire knowledge in area of specialty
• Be highly thorough and dependable
• Effectively coach and deliver constructive feedback

Responsibilities

• Deliver 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
• Collaborate with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions
• Consult on the design, development, and implementation of DevOps and ML Ops pipelines
• Lead portions of deployment processes under guidance from people leader
• Review, verify, validate, and troubleshoot code to ensure high availability and high performance of machine learning models and applications - debugging & defect management
• Use complex knowledge and understanding of code management principles and best practices to follow architectural and governance guidelines
• Effectively communicate and apply machine learning engineering value, concepts, and strategies across multiple scenarios

Preferred Qualifications

Have knowledge in insurance field

Benefits

• Medical, dental, and vision coverage
• Life insurance
• Long & short-term disability
• 401(k) retirement plans (with employer match)
• Tuition & certificate reimbursement
• Paid time off (vacation/sick/holidays)