Full Job Description
We are seeking a versatile and technically strong Software Engineer to help design, build,
and own end-to-end development of the internal tooling that supports imaging engineering
and quality workflows across Camera, Photos, and Image Quality. You will contribute to
multiple Swift applications, React-based web frontends, and Python REST API services, and
leverage Apple infrastructure to run asynchronous compute jobs.
The ideal candidate is an experienced generalist who is comfortable moving between client,
web, and backend code; has a solid grasp of distributed-systems fundamentals; and writes
code with an eye toward maintainability, correctness, and long-term operability. You are
equally at home designing a new service, debugging a tricky async job, polishing a UI
workflow, and sitting down with a partner team to understand what they actually need before
writing a line of code. You bring informed opinions about where AI genuinely improves a
system, and where it adds unnecessary complexity, and you hold AI-powered features to the
same engineering standards as any other production code. Above all, you are a strong
communicator who treats cross-functional collaboration as a core part of the job.
BS in Computer Science, Computer Engineering, or equivalent experience.
4+ years of professional software engineering experience shipping production software.
Proficiency in at least two of: Swift, Python, and JavaScript/TypeScript, with a track record
of contributing meaningfully in both client and server code.
Strong understanding of REST API design and experience building production REST
services.
Experience building web frontends with React or a similar framework.
Demonstrated experience integrating AI/ML models (LLMs, vision models, or similar) into
production software systems, not just as a user but as a builder responsible for reliability
and maintainability.
Working knowledge of asynchronous job execution patterns (background workers, task
queues, or similar) for long-running computations.
Solid understanding of software engineering fundamentals: data modeling, API design,
testing, debugging, and code review.
Strong written and verbal communication skills, with a demonstrated ability to work
effectively with partners outside of engineering.
Experience building production features with LLM APIs (e.g., OpenAI, Anthropic, or on-
device models), including prompt design, context window management, output validation,
and graceful degradation.
Familiarity with multimodal or computer vision models applied to image analysis, quality
assessment, or visual data retrieval, with an understanding of where these models succeed
and fail in practice.
Experience with vector databases or semantic search (e.g., pgvector, Pinecone, Weaviate)
for unstructured or high-dimensional data retrieval pipelines.
Understanding of MLOps principles: model deployment pipelines, versioning strategies,
evaluation frameworks, A/B testing for AI features, and production monitoring for model
quality and cost.
Awareness of bias and fairness considerations in AI systems, particularly in visual domains,
including diverse evaluation datasets, inclusive quality benchmarks, and responsible
deployment practices.
Experience developing native macOS or iOS applications in Swift, including familiarity with
Xcode.
Experience designing and operating distributed systems, including awareness of the
tradeoffs involved in consistency, coordination, and failure handling.
Familiarity with Solr (or other search platforms such as Elasticsearch) for indexing and
querying large datasets.
Familiarity with Redis, whether as a cache, message broker, or coordination primitive.
Comfort working with image data, metadata pipelines, or scientific/engineering workflows.
Exceptional cross-functional collaboration skills: stakeholder alignment, documentation,
and presenting technical work to non-engineering partners.
Comfortable and adaptable in a fast-paced environment with shifting priorities and multiple
stakeholders.
