Generative AI Applied Scientist, Applied Machine Learning
Job Description
Summary
We are seeking a highly skilled and motivated Applied ML Scientist with expertise in Generative AI to join our dynamic team. In this role, you will be responsible for developing innovative and practical AI applications that drive enterprise transformation. Your work will have a direct impact on optimizing operations, enhancing productivity, and fostering innovation within our organization. The Applied Machine Learning Data Science team in IS&T are a group of passionate applied ML scientists from various disciplines with extensive track records in both academia and industry.
We work on many high impact projects that serve various Apple lines of business. We are at the forefront of using sophisticated machine learning techniques and mathematical models to tackle impactful business problems. We continuously innovate and are constantly pushing the envelope. The Applied Machine Learning Data Science team is an outstanding combination of machine learning techniques, algorithms, as well as real world business solutions that will impact billions of devices in the world. Join us and you will have the opportunity to do groundbreaking applied machine learning work that will craft the industry.
We work on many high impact projects that serve various Apple lines of business. We are at the forefront of using sophisticated machine learning techniques and mathematical models to tackle impactful business problems. We continuously innovate and are constantly pushing the envelope. The Applied Machine Learning Data Science team is an outstanding combination of machine learning techniques, algorithms, as well as real world business solutions that will impact billions of devices in the world. Join us and you will have the opportunity to do groundbreaking applied machine learning work that will craft the industry.
Description
As an AML applied ML scientist, you will engage with Business Teams: Collaborate closely with business teams to identify opportunities, gain a deep understanding of their requirements, and effectively translate these requirements into innovative technical solutions.
Designing Generative AI Solutions: Lead the design and development of generative AI solutions. Utilize established techniques and, when necessary, create custom algorithms to tackle complex challenges effectively.
Collaborating with Cross-Functional Teams: Work closely with our team of engineers and platform architects to seamlessly integrate and deploy robust, enterprise-grade ML applications and systems that meet our business objectives.
Continuous Research and Innovation: Stay at the forefront of data science and machine learning advancements. Continuously explore and evaluate new technologies and methodologies to enhance the technical capabilities of our team, ensuring that we remain at the cutting edge of ML innovation.
Designing Generative AI Solutions: Lead the design and development of generative AI solutions. Utilize established techniques and, when necessary, create custom algorithms to tackle complex challenges effectively.
Collaborating with Cross-Functional Teams: Work closely with our team of engineers and platform architects to seamlessly integrate and deploy robust, enterprise-grade ML applications and systems that meet our business objectives.
Continuous Research and Innovation: Stay at the forefront of data science and machine learning advancements. Continuously explore and evaluate new technologies and methodologies to enhance the technical capabilities of our team, ensuring that we remain at the cutting edge of ML innovation.
Minimum Qualifications
- 5+ years of industry experience with strong ML fundamentals
- Hands-on experience with building Deep Learning applications
- Proficiency in using ML toolkits, e.g., PyTorch
- Strong analytical and problem solving skills
- M.S. or PhD in Electrical Engineering/Computer Science, or a related field (mathematics, physics, statistics or computer engineering) preferred
Preferred Qualifications
- Strong software engineering skills in Python to create scalable and robust infrastructure for deep learning data, modeling, and evaluation systems
- Proven ability to train and debug deep learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework
- Familiarity with researching current ML literature and math including optimization methods and modeling techniques
- Strong experience in the transition of a prototype into a final product
- Excellent written and verbal communications skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams