Engineering Manager, Model & Algorithm Evaluation & Quality, Sensing & Connectivity

Apple • Cupertino, CA

13h

About The Position

Join Apple’s Sensing and Connectivity - Location Context team, which develops personalized insights from users’ daily patterns through multimodal sensing and AI models. The team combines machine learning—including integration, adaptation, and tuning of foundation models—with contextual sensing and study design to derive insights for products such as Maps, Fitness, and Journal. The role leads the team responsible for the quality of location intelligence features powered by machine-learning models across operating systems including iOS and watchOS. The team develops science-backed AI/ML models that capture aspects of human health and behavior and deliver insights to customers.

The Engineering Manager leads engineers evaluating algorithms and AI models behind location context features and owning quality engineering for shipped software, including test automation, software testing, and continuous integration. The work takes place in a fast-paced environment closely connecting evaluation and development. The manager will evaluate probabilistic, on-device models, defining correctness when ground truth is scarce and real-world behavior cannot be fully simulated.

The manager owns model evaluation and end-to-end quality strategies, sets the team’s technical direction, and leads automation, continuous integration, analytics, and monitoring. The role establishes success metrics and communicates results in technical, user-study, data-review, engineering, and executive settings. It also drives issue resolution with partner teams, coordinates end-to-end quality with development and program management across release schedules, sets the team’s future vision, and hires, coaches, mentors, and develops engineers.

Requirements

• BS, MS, or PhD in Computer Science, Electrical Engineering, or equivalent.
• At least 5 years of relevant industry experience.
• At least 2 years leading and managing an engineering team, with a track record of growing engineers’ skill sets and creating meaningful career growth.
• Experience evaluating AI/ML models, including crafting benchmarks and evaluation protocols and performing statistical analysis.
• Proficient in designing AI-assisted workflows and using generative AI to automate and accelerate testing, debugging, and metrics analysis.

Nice To Haves

• Hands-on engineering background with enough software development experience to set technical direction and critically evaluate the team’s work.
• Experience evaluating foundation models or large language models, such as building evaluation harnesses, golden datasets, LLM-as-judge pipelines, or human-in-the-loop evaluation.
• Experience with sensor, time-series, or on-device machine-learning models and the data pipelines behind them.
• Experience building or leading automation, test infrastructure, and continuous-integration systems.
• Experience working at the intersection of hardware and software.
• Ability to work in a dynamic environment with shifting priorities and schedules, with excellent analytical, problem-solving, and communication skills.

Responsibilities

• Own model evaluation strategy for machine-learning models and other algorithms, including benchmarks, evaluation protocols, and validation of training data, features, and labels, as well as quality strategy for the end-to-end experiences they power.
• Set the technical direction for model evaluation, challenge design and implementation, translate model-output assessments into prioritized algorithm improvements, and ensure rigor in the team’s analysis and conclusions.
• Lead development of automation, continuous integration, analytics, and monitoring to qualify features, measure performance and system memory usage, and track quality across releases.
• Identify project-success KPIs, build supporting dashboards, and represent results in user-study, code, and data reviews and to engineering and executive audiences.
• Drive bug resolution across the broader software engineering organization and Apple partner teams, escalating and negotiating as needed to maintain quality.
• Work with development, program management, and cross-functional partners from upstream hardware to downstream apps to deliver end-to-end quality aligned with release schedules.
• Set a vision for the team’s future direction, identify new opportunities, and build stakeholder support for pursuing them.
• Hire, coach, mentor, and grow the team, building on individual strengths and supporting meaningful career growth.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager