AIML - Staff Software Engineer, On-Device Machine Learning

Key Skills

Aartificial intelligence, Analytical and Problem solving, C Programming, C++, CUDA kernels, Effective communication skills, GPUs, Large Language Models - LLMs, Machine learning techniques, Python Programming, PyTorch, TensorFlow

Job Description

Are you someone who can write high-quality, well-tested code and collaborate cross-functionally with partner HW, SW and ML teams across the company? If so, come join us and be part of the team that is helping Machine Learning developers innovate and ship enriching experiences on Apple devices!

Key Qualifications

• 10-15+ years proven programming skills using standard ML tools such as C/C++, Python, PyTorch, Tensorflow, CUDA/Metal.
• Solid understanding of state-of-the-art DNN optimization techniques and how they translate to hardware acceleration architectures, and a general ability to reason about system performance (compute/memory) tradeoffs
• Hands-on experience working (training, fine-tuning, optimizing, deploying) with large models (e.g. LLMs).
• Hands-on experience applying common machine learning optimization techniques, like quantization and sparsity-induction, to reduce the resource consumption and/or eliminate latency
• Experience building APIs and/or core components of ML frameworks
• Capacity to iterate on ideas, work with a variety of partners from all parts of the stack — from Apps to Compilation, HW Arch, and Power/Performance analysis
• Proven track record to analyze sophisticated and ambiguous problems
• Disciplined programming abilities with a strong attention to detail
• Strong applied experience with compiler technology to work with CPU, GPU, and ML accelerators
• Excellent problem-solving (e.g. via building forward-looking prototype systems), critical thinking, strong communication, and collaboration skills

As a member of this team, the successful candidate will: 

- Build features for our on-device inference stack to support the most relevant accuracy preserving, general purpose techniques that empower model developers to compress and accelerate SoTA models (e.g., LLMs) in apps

- Convert models from a high-level ML framework to a target device (CPU, GPU, Neural Engine) for optimal functional accuracy and performance

- Write unit and system integration tests to ensure functional correctness and avoid performance regressions

- Diagnose performance bottlenecks and work with HW Arch teams to co-design solutions that further improve latency, power, and memory footprint of neural network workloads 

- Analyze impact of model optimization (compression/quantization etc) on model quality by partnering with modeling and adaptation teams across diverse product use cases.

Education & Experience

Bachelor’s, Master's, or PhD in Computer Science, Machine Learning or a related field

Pay & Benefits

• 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 $199,800 and $364,100, 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.