Sr Machine Learning Engineer - Large Language Models & Generative AI Platform & Infrastructure
Job Description
Summary
Imagine what you could do here. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s 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.
We are looking for a highly skilled and experienced Sr Machine Learning and Generative AI engineer who has a robust understanding of Large Language Models and Generative AI to help work on exciting technologies for future Apple products and bring it to live. In this role, you will join a team of machine learning engineers with different specialization to discover and build solutions to previously-unsolved challenges and push the state of the art for global audience.
You will collaborate with cross-functional teams of business SMEs, engineers, data scientists, designers, and researchers. This role is exceptionally technical, and will require you to actively engage in all aspects of the work, from conceptualization and theoretical considerations to design, coding, and implementation.
We are looking for a highly skilled and experienced Sr Machine Learning and Generative AI engineer who has a robust understanding of Large Language Models and Generative AI to help work on exciting technologies for future Apple products and bring it to live. In this role, you will join a team of machine learning engineers with different specialization to discover and build solutions to previously-unsolved challenges and push the state of the art for global audience.
You will collaborate with cross-functional teams of business SMEs, engineers, data scientists, designers, and researchers. This role is exceptionally technical, and will require you to actively engage in all aspects of the work, from conceptualization and theoretical considerations to design, coding, and implementation.
Description
In this role, you will focus on the following key areas:
- You’ll work in a team of machine learning engineers of different specialization to prototype and ship world class algorithms that pushes the state of the art.
- Lead the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields.
- Lead MLOps, automating ML pipeline, including the training, testing, deployment, monitoring, and scaling of AI models.
- Turn prototypes into automation pipelines and deploying them to production; deciding
when to use out-of-the-box solutions vs. building custom solutions and utilizing both.
- Ongoing data analysis to build new or fine-tune existing models such as GPT to optimize results.
- Partner closely with software engineers to implement these models into high-performing systems and models in our production environment that can be applied to create amazing experience for our worldwide audience.
- Actively engage in all aspects of model development, from ideation and experimentation to deployment.
- Communicate results of analyses to business partners and executives
- Maintain expertise in the latest advancements in AI technology. Partner with your team members to prepare presentations, papers, and patents for your inventions.
- Proactively address and reduce potential biases in model predictions, ensuring our products are inclusive and fair.
- Design and implement efficient data pipelines to support large language model training and inference.
- You’ll work in a team of machine learning engineers of different specialization to prototype and ship world class algorithms that pushes the state of the art.
- Lead the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields.
- Lead MLOps, automating ML pipeline, including the training, testing, deployment, monitoring, and scaling of AI models.
- Turn prototypes into automation pipelines and deploying them to production; deciding
when to use out-of-the-box solutions vs. building custom solutions and utilizing both.
- Ongoing data analysis to build new or fine-tune existing models such as GPT to optimize results.
- Partner closely with software engineers to implement these models into high-performing systems and models in our production environment that can be applied to create amazing experience for our worldwide audience.
- Actively engage in all aspects of model development, from ideation and experimentation to deployment.
- Communicate results of analyses to business partners and executives
- Maintain expertise in the latest advancements in AI technology. Partner with your team members to prepare presentations, papers, and patents for your inventions.
- Proactively address and reduce potential biases in model predictions, ensuring our products are inclusive and fair.
- Design and implement efficient data pipelines to support large language model training and inference.
Minimum Qualifications
- 5+ years building NLP/AI software professionally and successfully releasing to customers.
- 5+ years of hands-on experience in building scalable systems for training & evaluating of machine learning/deep learning models.
- Experience with state-of-the-art NLP algorithms and AI models, Multi-modal LLMs, Multi-modal contrastive learning, Foundation models, Diffusion based models and parameter efficient fine tuning of LLMs.
- Familiarity with deploying model for large scale inferencing & optimizations.
- Solid understanding of inference speed up techniques such as speculative decoding and optimization of LLMs for human preferences.
- A strong track record of shipping products and publications / patents.
- Strong proficiency in PyTorch, TensorFlow, Transformers, Kubernetes, Docker, LangChain, vectorDB and cloud platforms like AWS, GCP, or Azure, and Monitoring tool like Grafana, and CI/CD like airflow, gitlab, and Big Data management like Spark, Kafka.
Preferred Qualifications
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning or related field; or M.S. in related field with 3+ years experience applying machine learning engineer to real business problems.
- Excellent presentation, written and verbal communication, engagement and interpersonal skills along with validated skills in building great design.
Pay & Benefits
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