Principal Applied Data Scientist

Responsibilities

As part of theOCI Gen AI and Data Solutionsfor strategic customersteam, you will be responsible for developing innovative Gen AI and data services for our strategic customers.As a Principal Applied Data Scientist, you'll lead the development of advanced Gen AI solutions using the latest ML technologies combined with Oracle's cloud expertise. Your work will significantly impact sectors like financial services, telecom, healthcare, and code generation by creating distributed, scalable, high-performance solutions for strategic customers.

• Work directly with key customers and accompany them on their Gen AI journey understanding their requirements, help them envision and design and build the right solutions and work together with their ML engineering to remove blockers.
• You will dive deep into model structure to optimize model performance and scalability.
• You will build state of art solutions with brand new technologies in this fast-evolving area.
• You will configure large scale OpenSearch clusters, setting up ingestion pipelines to get the data into the OpenSearch.
• You will diagnose, troubleshoot, and resolve issues in AI model training and serving. You may also perform other duties as assigned.
• Build re-usable solution patterns and reference solutions / showcases that can apply across multiple customers.
• Be an enthusiastic, self-motivated, and a great collaborator.
• Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc.

Qualifications and experience

• Bachelors or masters in computer science or equivalent technical field with 10+ years of experience
• Able to optimally communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations).
• Demonstrated experience in designing and implementing scalable AI models and solutions for production,relevant professional experience as end-to-end solutions engineer or architect (data engineering, data science and ML engineering is a plus), with evidence of close collaborations with PM and Dev teams.
• Experience with OpenSearch, Vector databases, PostgreSQL and Kafka Streaming.
• Practical experience with setting up and finetuning large OpenSearch Clusters.
• Experience in setting up data ingestion pipelines with OpenSearch.
• Experience with search algorithms, indexing, optimizing latency and response times.
• Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts.
• Familiarity with Agents and Agent frameworks and Model Predictive Control (MPC)
• Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc.
• Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences.
• Ability and passion to mentor and develop junior machine learning engineers.
• Proficient in Python and shell scripting tools.

Preferred Qualifications:

• Masters or Bachelor's in related field with 5+ years relevant experience
• Experience with RAG based solutions architecture. Familiarity in OpenSearch and Vector stores as a knowledge store
• Knowledge of LLM and experience delivering, Generative AI And Agent models are a significant plus.
• Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus.
• Experience with semantic search, multi-modal search and conversational search.
• Experience in working on a public cloud environment, and in-depth knowledge of IaaS/PaaS industry and competitive capabilities.Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc.
• Experience with LLM fine-tuning, especially the latest parameter efficient fine-tuning technologies and multi-task serving technologies.
• Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers.
• Experience with deep learning frameworks (such as PyTorch, JAX, or TensorFlow) and deep learning architectures (especially Transformers).
• Experience in diagnosing, fixing, and resolving issues in AI model training and serving.