About Flatiron School As a leader in the tech industry, Flatiron School believes that education is the best investment you can make in your future. We’re committed to helping change lives and the world for the better. Our courses provide an immersive, outcomes-driven curriculum for students looking to launch a career in Software Engineering, Cybersecurity, Data Science, Artificial Intelligence and Game Design. In addition to student programs, we also offer targeted education solutions for organizations. Our Mission: Enabling the pursuit of a better life through education Our Values: Make No Little Plans - Build for scale, create for the future, execute short-term goals in view of long-term strategy Radiate Positivity - Be kind, have fun, find what to love Strive for Excellence - Drive results, hold yourself and each other accountable to our shared goals Be a Lifelong Learner - Embrace a growth mindset, be curious, get comfortable with being uncomfortable Work Together - Collaborate, embrace transparency, empower others to succeed Nurture Difference - Seek to understand, notice who or what is missing, actively seek out different opinions, create space for other voices to be heard About the Opportunity Flatiron School is offering a paid, work-integrated apprenticeship for professionals with general work experience (2+ years in any field) who want to transition into their first role in software engineering. This program is designed for career switchers who are new to tech or have only foundational exposure. You’ll learn in-demand technical skills through Flatiron’s bootcamp programs while gaining real, paid industry experience with an employer partner. What You'll Do Complete Flatiron School’s Software Engineering (full-time) and AI & Data Science (part-time) bootcamp programs Contribute to real software projects during a paid apprenticeship with an employer partner Collaborate in sprint-based workflows and participate in code reviews Build a portfolio of production-level work Receive mentorship from experienced engineers and product leaders What You’ll Learn Foundations of software development and modern engineering practices How software engineering and data intersect in AI-enabled products Agile development workflows and team collaboration Writing clean, maintainable, production-quality code Applying data-informed thinking to engineering problems Who This Program Is For Professionals with 2+ years of work experience in any field Career switchers seeking their first professional role in tech Candidates excited to learn, collaborate, and grow in a structured environment This Program Is Not For Experienced software engineers, developers, or data scientists Candidates with prior professional experience in technical engineering roles Program Details Commitment: Full-time (40 hours/week) for 18 months Phase 1 (4 months): Full-time coursework Phase 2 (14 months): 20 hrs/week paid apprenticeship 20 hrs/week part-time coursework Compensation: $15/hour for 20 hrs/week (starting month 5) Tuition: $19,500 (covered through an installment plan during the program) Location: U.S.-based candidates only Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship) Requirements

• Lead and grow a team of ML engineers focused on production ML systems • Lead model improvements in response to production issues, product feedback, and new research or platform advancements • Lead production release processes for ML services, including release planning, CI/CD, staged rollouts, and rollback procedures • Build and operate observability and on-call practices for ML features, including monitoring, alerting, dashboards, incident response, and post-incident reviews • Develop and maintain scalable evaluation frameworks, datasets, and automated regression tests to prevent quality regressions • Lead reliability, performance, and cost improvements for inference and serving, including capacity planning and meeting SLAs (latency, throughput, availability) • Partner with researchers, product, and platform teams to define quality bars and production readiness, including Trusted AI requirements • Establish and evolve production standards and governance across ML features (testing, evaluation methodology, release gates, model versioning and lineage) • Partner with platform and product teams to integrate ML capabilities into products

• Manage, support, and mentor a diverse group of engineers • Give engineers the tools, confidence, and motivation to make choices that result in recognition for themselves and not just for yourself • Remove roadblocks for your team and escalate when you need additional context or direction • Drive your team toward their career goals, identify milestones, and set them up for success along the way • Promote a culture of feedback and transparent communication • Partner with internal stakeholders on feature definition and drives breakdown of work to support organization objectives • Partner closely with the management team, HR, and Recruiting to attract, recruit, and develop a diverse team of high-quality engineers • Proactively maintain alignment between business goals and objectives with the team's day-to-day work • Work to resolve or escalate issues that serve as roadblocks and place deliverables and goals at risk • Gain and maintain visibility into trade-offs between options and priorities to positively influence the approach taken by the team • Design feedback loops to incorporate members' feedback into continuous improvement activities

• Lead two high-impact mobile pods: Mobile Platform and Mobile Product • Define and evolve cross-platform strategy • Improve build systems and developer productivity • Establish performance SLOs • Drive architectural simplification and introduce AI-assisted SDLC tooling • Lead customer-facing feature development • Partner closely with Product & Design • Manage ~13-14 engineers across 2 pods • Hire and retain high-performing mobile engineers • Establish measurable KPIs and ensure predictable sprint delivery