• Lead and develop a team of software engineers through clear context, mentorship, and structured feedback. • Stay hands-on in architecture and delivery, contributing to design decisions and production code. • Partner with Product and Design to translate priorities into well-scoped, executable plans. • Break down complex initiatives into milestones that support predictable, high-quality delivery. • Maintain strong engineering standards across code quality, testing, documentation, and operational reliability. • Identify and address technical risks and process gaps before they impact delivery. • Help hire and grow the team thoughtfully as Fixify scales.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves leading an innovative team responsible for enhancing the data lifecycle that supports machine learning processes. - Set and execute the technical strategy aligned to metrics such as increasing data evaluation velocity. - Establish clear end-to-end ownership across the data lifecycle. - Accelerate third-party data onboarding through standardized practices. - Drive data quality frameworks to prevent launch issues. - Unlock internal data for ML innovation by improving metadata coverage. - Champion a company-wide shift towards data contracts and SLAs. - Build and lead a high-performing team in data integration and infrastructure. Qualifications - Bachelor’s degree in Computer Science, Engineering, or Mathematics, or related field. - 8 years of engineering experience, with 3 years in a management role. - Proven experience in building and scaling data platforms for ML workflows. - Demonstrated ownership of cross-functional engineering initiatives. - Experience designing and enforcing data quality frameworks and SLAs. - Strong technical foundation in modern data stacks and architectures. Benefits - Competitive compensation package including salary, bonuses, and equity grants. - Generous 401(k) with matching contributions. - Employee Stock Purchase Plan (ESPP) with discounts on stock. - Affordable medical, dental, and vision coverage. - Health Savings Account contributions. - Paid time off, family leave, and company holidays. - Annual wellness and productivity allowances. - Employee Assistance Program (EAP) for mental health support.

• Lead and grow backend and ML engineering teams (25+ engineers) • Own the unit's delivery commitments (sprint, quarter) and ensure predictable execution against them • Partner with PMs and TLs to translate product goals into realistic roadmaps • Design, evolve, and enforce team processes • Track delivery health using metrics and drive continuous improvement • Ensure teams meet agreed SLOs and reliability targets • Build a culture of constructive feedback, psychological safety, and engineering excellence across the unit • Report progress, risks, and staffing needs to Engineering Leadership in a clear, structured way

• Lead and grow multiple client engineering teams; own headcount planning, hiring, performance management, and career development for engineers across the unit • Own the unit’s release calendar and delivery commitments; drive predictable release cadence across all platforms (Quest, AVP, WebXR, mobile) • Manage app store submission pipelines - coordinate builds, certification, compliance requirements, and release rollouts across Meta Quest Store, Apple App Store, and Google Play • Partner with PMs and TLs to translate product goals into realistic release plans; manage scope and cut decisions when timelines are at risk • Coordinate cross-team and cross-unit dependencies - ensure Platform API contracts, QA test cycles, and DevOps pipelines align with release schedules • Design, evolve, and enforce team processes - sprint planning, stand-ups, retrospectives, build/release workflows, and incident response • Track delivery health using metrics (throughput, lead time, predictability rate, crash-free rates, app store rejection rates) and drive continuous improvement • In cooperation with DevOps and QA, ensure teams meet quality gates and performance targets before each release • Build a culture of constructive feedback, psychological safety, and engineering excellence across the unit • Report progress, risks, and staffing needs to Engineering Leadership in a clear, structured way