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Apple Sales - AI Architect LLM & Gen Singapore 24486544
21.04.2025
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You will collaborate with multi-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, you will be responsible for running 1000 steps ahead, looking around the corner, and help bridge the gap between business and technical teams, ensuring that the technical architecture and solutions aligned with strategic goals and deliver measurable business values and KPIs.
In this role, you will focus on the following key areas:- You’ll be working in a team of machine learning engineers of different specializations to prototype and ship world class algorithms that are state of the art.- Lead the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields, including multi modal capabilities.- 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.- Actively engaging in all aspects of model development, from ideation and experimentation to deployment.
- 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.
- Experience in identifying and delivering state-of-the-art product architecture for our end to end solutions.
- 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.
- Experience with Cloud technologies and familiarity with AWS & GCP.
- 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.
- 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.
- 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.
- A thought leader having a good balance of business insight, domain and technical expertise.
- Excellent presentation, written and verbal communication, engagement and interpersonal skills along with validated skills in building great design.
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