Apple logo

Sr.Software Engineer (Machine Learning), Ops & Sales Engineering

Apple

Sunnyvale, CAJobSeen 1w agoSeen in employer's feed 1 day ago

Most applications go out cold — see where you stand first. No sign-up to start.

Watch jobs like this.

At a glance

Compensation
No compensation found
Location
Sunnyvale, CA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Master's degree

Job overview

Apple seeks a dynamic, highly motivated Applied Machine Learning Engineer with GenAI expertise to develop scalable, value‑driven ML solutions for its global sales and operations engineering team, tackling complex supply chain challenges within an enterprise context.

Skills & qualifications

RequiredNice to have

Skills

PythonMachine LearningML DeploymentC++TensorFlowPyTorchDeep LearningNLPAnomaly DetectionLarge Language ModelsGenerative AIRetrieval Augmented GenerationFine TuningPrompt EngineeringAgentic SystemsTool UsePlanningOrchestrationHuman in the LoopUncertainty EstimationConfidence EstimationRobustnessFactualitySafetyLatencyCostSQLSparkGraph DatabasesCloud PlatformsMLOpsReinforcement LearningCommunication

Qualifications

MS in Computer Science or Related FieldPhD in Computer Science or Related Field5+ Years Industry Experience Developing Machine Learning Solutions10+ Years Experience Building and Deploying Production Machine Learning Systems Using Python C++ Tensorflow or PytorchExperience Deploying ML Solutions to Production

Full job description

Role Number: 200685752-3956

Summary

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Itʼs the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it!

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS&T) organization. IS&T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS&T makes the impossible feel effortless.Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here.

Description

Sales and Operations Engineering is part of IS&T and drives the technology behind Apple's global operations, sales, and supply chain. The team connects the systems that move products from factory to customer — bridging sales platforms with the operational infrastructure that keeps Apple running at scale and ensuring Apple's technology and business priorities move in lockstep.

We are looking for a dynamic, highly motivated, experienced Applied Machine Learning Engineer, with expertise and experience in GenAI, for the Advanced Analytics team to join the IS&T Sales and Ops Engineering.

At Apple, the increasing supply chain complexity and scale presents unique challenges. This role is focused on applying GenAI and Machine Learning technologies to solve complex supply chain challenges within an enterprise context. The ideal candidate will have a proven track record of delivering scalable, value-driven ML and GenAI solutions. You will be working with a team of experts responsible for designing and developing solutions leveraging advanced analytics (optimization, ML, simulation and GenAI) from strategic to executional decision-making and with engineering and application teams to integrate these solutions into our existing systems.

Minimum Qualifications

  • MS in Computer Science, Machine Learning, Applied Math or a related field.

  • 5+ years of industry experience developing Machine Learning Solutions.

  • Hands on experience in Python as programming language.

  • Experience deploying ML solutions to production.

Preferred Qualifications

  • PhD in Computer Science, Machine Learning, Applied Mathematics, or a related field.

  • 10+ years of experience building and deploying production machine learning systems using Python, C++, TensorFlow, or PyTorch.

  • Deep expertise in machine learning, deep learning, NLP, anomaly detection, large language models, and Generative AI, including modern architectures, retrieval-augmented generation, fine-tuning, prompt engineering, and agentic systems.

  • Experience designing, deploying, and evaluating reliable AI and agentic systems, including tool use, planning, orchestration, human-in-the-loop controls, uncertainty and confidence estimation, robustness, factuality, safety, latency, cost, and end-to-end business outcomes.

  • Experience with scalable data and ML infrastructure, including SQL, Spark, graph databases, cloud platforms, and MLOps.

  • Experience applying reinforcement learning, NLP, and Generative AI to operational, logistics, or supply chain problems.

  • Proven ability to independently deliver high impact AI solutions from concept through production, define meaningful KPIs, and measure business impact.

  • Excellent communication and collaboration skills, with the ability to explain complex technical concepts clearly, work effectively across technical and business teams, and build alignment around AI initiatives.

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.

Similar jobs, posted recently

Open roles like this one, listed in the last 30 days.

You've read the whole posting — now see how you match it.