Sr. Software Development Engineer (Applied ML)-Hardware Product Design

As a senior member of this team, you will design, build, and own ML systems end-to-end for ADL’s machining, design-for-manufacturing, and related engineering workflows, including the architectural calls about which approach fits a given problem and when to retire one that isn’t scaling. You’ll work directly with the people running those workflows: understanding their constraints, building tools they trust, and iterating with tight feedback loops. You’ll choose the right tool for each job (classical statistics, classical ML, deep learning, generative AI, or pure algorithmic approaches) and make sure others understand your logic.
The DataViz team is small. You’ll be the senior ML IC partnering with data scientists and visualization engineers on our side, with engineers and machinists on the ADL side, and with a partner engineering team that contributes to the broader system. Expect real autonomy on the architectural calls, and real accountability for whether the systems you ship still work six months later.
We don’t expect any one candidate to bring every qualification below. What we care about most is the kind of thinking you bring to hard problems: clarity about what you do and don’t know, and the patience to work through ambiguity (and change your mind when the evidence asks you to). If that resonates, we’d love to hear from you.

Own ML systems end-to-end (problem framing through deployment) for ADL’s machining, design-for-manufacturing, and related engineering workflows.
Architect multi-component AI workflows: how models, agents, and rule-based components compose, where boundaries should sit, and how the pieces stay debuggable as the system evolves.
Work with 3D geometric data (CAD files) including reasoning about geometry as a first-class input to models rather than a side channel.
Select and apply the right modeling approach per problem.
Establish evaluation and monitoring strategies that survive contact with messy real-world data, including offline benchmarks, automated checks, and human-in-the-loop review.
Communicate trade-offs, system behavior, and limitations clearly to technical and non-technical audiences.

Bachelor’s + 7 YOE, Master’s + 5 YOE, or PhD + 2 YOE (or equivalent professional experience) in CS, Math, Statistics, Physics, Engineering, Robotics, or a similar analytical field, with the bulk of those years building ML systems in production or applied settings.
Strong Python skills and fluency with the standard ML stack. Practical fluency with using and evaluating modern foundation models (LLMs, VLMs) in production matters more than depth in any one training framework.
Full-lifecycle ML experience covering problem framing, data work, training, evaluation, and iteration with real users, including the judgment to know when ML isn’t the right tool at all.
Hands-on experience designing or extending agentic AI systems (multi-step, tool-using workflows where models plan, act, and recover) and the evaluation frameworks that keep them reliable — including ground truth that is contested, expensive, or partial, and small labeled datasets.
Comfort collaborating with non-ML domain experts: drawing out tacit expertise that may never have been written down, translating their constraints into modeling decisions, and communicating results back in their terms.

Familiarity with 3D geometric data formats (STEP, mesh, BRep) or 3D libraries such as OpenCASCADE, Trimesh, or PyTorch3D.
ML applied in engineering, manufacturing, machining, or other physical-world domains where models interact with hardware that has real-world constraints.
Building reliable, user-facing features or workflows backed by LLMs, VLMs, or other GenAI models, particularly where visual or geometric inputs matter.
Algorithmic depth relevant to manufacturing software: computational geometry, graph algorithms, constraint satisfaction, tool-path generation, or CAD/CAM internals.

We’re looking for a senior AI/ML engineer to do applied ML at the intersection of 3D geometry, manufacturing process, and the tacit expertise of the people who run that process. You’ll join the Data Science and Visualization (DataViz) team in Hardware Engineering at Apple, working day-to-day in close partnership with Apple’s Advanced Development Lab (ADL) to bring machine learning into the heart of their machining and prototyping workflows.
Much of this work sits at the intersection of two things: CAD files that describe the parts ADL manufactures, and process knowledge that lives in the heads of engineers and machinists rather than in any document. Your job is to work with partners to surface that tacit expertise, encode it into tools they can rely on, and keep those tools honest with disciplined evaluation.

At Apple’s ADL (Advanced Development Lab), we seamlessly blend our expertise and creativity to deliver remarkable results that swiftly translate into exceptional products and customer experiences. We invite you to bring your visionary thinking and unwavering dedication to our esteemed organization. As a dynamic group of individuals, we take great pride in our work. Our specialized focus lies in crafting high-quality models, prototypes, and manufacturing/design solutions.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Apple accepts applications to this posting on an ongoing basis.