New CS Grads - Software Engineer Apprenticeship at Flatiron School

, , United States -

Full Time

Start Date

Immediate

Expiry Date

31 May, 26

Salary

20.0

Posted On

02 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, AI, Software Development, JavaScript, Python, Java, SQL, NoSQL, Agile Development, Code Reviews, Debugging, Testing, Feature Development, QA Processes, Machine Learning, Full-Stack Development

Industry

Description

About the Opportunity Flatiron School is offering an apprenticeship opportunity for early-career developers to earn income while learning. Apprentices will enroll in Flatiron’s AI and Data Science part-time bootcamp and be matched with one of our employer partners for a paid apprenticeship throughout the duration of your course. This is a unique opportunity to develop skills in AI and data science while gaining hands-on industry experience. As an apprentice, you’ll contribute to software products, collaborate with experienced engineers, and build your portfolio with production-ready work. At the same time, you’ll deepen your understanding of data and machine learning to become a more versatile, full-stack software developer. This is a full-time opportunity, 40 hours/week (20 hours coursework and 20 hours apprentice work) for a 14-month program. The apprenticeship earnings will cover the tuition cost of the bootcamp. What You'll Do Attend and complete the part-time Data Science Bootcamp as part of the apprenticeship Contribute to software projects for your host company Write clean, maintainable and testable code using modern frameworks and tools Collaborate in sprint-based workflows and participate in code reviews Support feature development, debugging, documentation, and QA processes Build your portfolio of production-level work while growing your technical and collaborative skills Receive ongoing mentorship from senior developers and product leaders What You'll Learn How engineering and data science intersect in modern AI products Practical agile development workflows in a collaborative environment Best practices for writing clean, maintainable, production-quality code How to build and ship features with real user needs and product strategy in mind How to apply data thinking to software engineering challenges What We're Looking For Requirements: Must be currently living in the U.S. Must be authorized to work in the U.S. We do not offer any visa sponsorship at this time - including H-1B, STEM OPT, and F-1 visa transfers. Must be available 40 hours/week for 14 months to complete the Flatiron School Data Science Bootcamp and for apprenticeship work Have a degree in Computer Science, Data Science/Analytics, Mathematics, or Economics OR have recently completed a software engineering bootcamp (strongly preferred); self-taught developers are also encouraged to apply Programming proficiency in at least one modern language (e.g., JavaScript, Python, Java) Familiarity with frontend and backend web development concepts Working knowledge of databases (SQL or NoSQL) and how to query or integrate them Preferred Skills: Awareness of testing, debugging, and code review practices Strong communication and collaboration skills Accountability in managing time and meeting small milestones Curiosity, initiative, and a strong desire to grow into a multidisciplinary developer Compensation & Commitments Hourly Pay: $20/hour for 20 hours/week paid through an employer partner (hiring entity) on their internal payroll cadence, 14-month commitment Tuition Coverage: Commit to pay the full $11,900 bootcamp tuition, through a monthly installment payment plan to Flatiron School Hours: 40 hours per week total - 20/week in apprenticeship role, 20/week in part-time bootcamp courses

Responsibilities

Apprentices will attend and complete a part-time Data Science Bootcamp while contributing to software projects for a host company, writing clean, maintainable code within sprint-based workflows. Responsibilities also include supporting feature development, debugging, documentation, and participating in code reviews to build a portfolio of production-level work.