SUMMARY

Posted: Jun 18, 2024
Role Number:200549023
Do you want to play a part in the next revolution in large languages models, contribute to products that are redefining mobile and desktop computing, and work with the people who built the intelligent assistant and search products that helps millions of people get things done - just by asking or typing? The vision for the AIML Data organization is to improve products by using data as the voice of our customers. As a Sr Machine Learning Engineer on the team, you will build algorithms and data applications that leverage the power of data (real and synthetic) to improve model training efficiency and performance.

DESCRIPTION

We are looking for people with a track record in building products and relationships to affect decisions. Join us, and impact hundreds of millions of customers across billions of their interactions with intelligent features on iPhone, iPad, HomePod, Mac, Watch, CarPlay, and tv across more than 30 languages. You will partner closely with data engineering and data science parters as well as product teams to identify areas for product and model quality hillclimb. Develop micro-services that enable easier, programmatic integration of model training processes and frameworks across the AIML organization. Use appropriate modeling techniques (large model fine-tuning included) to extract high value training datasets, verified through ablation studies. Apply ML rigor and complex algorithms in high impact projects. Evangelize findings throughout the organization to ensure integration of information into operational processes.

KEY QUALIFICATIONS

• Derive engineered metrics and statistical information out of massive and complex datasets (e.g. Spark MLlib, Druid, Solr, Kafka).
• Have built robust feature extraction and ML training pipelines and have a keen eye for where to automate (e.g. Airflow).
• Have done prototype-to-production development of ML models. You care about improving training performance by researching into the latest algorithms. You also value scaling inferences by applying CPU/GPU resources in parallelized fashion and have a strong foundation in data structures and optimization algorithms.
• Are knowledgeable in classic machine learning algorithms (SVM, Random Forest, Naive Bayes, KNN etc). Good understanding of bias/variance trade-off, regularization, dimension reduction.
• Have expertise in modern deep learning techniques via packages such as PyTorch, Keras/Tensorflow.
• Care about data generating processes, not just modeling them, but understanding the actual human and computational behavior from which data emerges.
• Are proficient in at least one programming language (e.g. Python, Golang) and are comfortable developing code within a team environment (e.g. git, testing, code reviews).
• Are self-motivated and curious. You continue to learn on the job.
• Have demonstrated creative and critical thinking with an innate drive to improve how things work.
• Have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.
• Can influence decisions with excellent verbal and written communications skills.

EDUCATION & EXPERIENCE

B.S. or advanced degrees in Computer Science, Electric Engineering or other related engineering programs.

Please refer the Job description for details