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Applied Scientist 2/3

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Oracle

3mo ago

  • Job
    Full-time
    Mid & Senior Level
  • Data
    Software Engineering

AI generated summary

  • You should have a PhD/Master’s in a related field, 3-5 years of ML experience, proficiency in Python/R and deep learning libraries, expertise in NLP and LLMs, and strong statistical model skills.
  • You will design and build generative AI models, implement cutting-edge techniques, optimize for production, develop code for model serving, and participate in the software lifecycle and operational tasks.

Requirements

  • Ph.D. degree or Master’s degree or equivalent experience in computer science, artificial intelligence, machine learning, operations research, or related technical field.
  • 5+ years w/Masters or 3+ years w/PhD of applying machine learning for solving real-world problems in industry
  • Proficiency in Python or R
  • Proficiency with at least one deep learning library (Pytorch, Tensorflow or Keras) with building and deploying DNN models in production.
  • Expertise in NLP, Transformers, Large Language Models, hugging face library. Optimizations around LLM training and serving.
  • Experience applying statistical models and developing Machine Learning solutions (regression, classification, clustering)
  • Extensive experience with developing and serving large scale Deep learning models across different data domains.
  • Experience in optimization and scaling of ML solutions for real world business use cases.
  • Expertise in statistical concepts and experience with traditional ML libraries such as scikit-learn, statsmodels and pandas
  • Past delivery of large-scale ML solutions for complex business problems
  • Experience with production operations and good practices for putting quality code in production and troubleshoot issues when they arise
  • Take initiative and be responsible for delivering complex software by working effectively with the team and other stakeholders
  • Can easily communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations)

Responsibilities

  • Design and build the world-class Generative AI Models in text, vision and multimodal setting for generating synthetic data.
  • Research and Implement cutting edge techniques(Fine tuning, RLHF) in aligning Generative models to specific problem domains.
  • Build the necessary tooling for data acquisition, data cleaning, data augmentation, model training and visualization.
  • Evaluate and Implement the ML/Deep learning/GenAI models from research papers and other public internet resources.
  • Optimize models for production usage and help productizing the generation scenarios to a production stetting.
  • Develop production code for feature processing, model prediction, serving, and monitoring in both real-time and batch scenarios.
  • Participate in the entire software lifecycle – development, testing, CI and production operations
  • Balance between product feature development and production operational concerns like writing run books, ops automation, structured logging, instrumentation for metrics and events

FAQs

What is the job title for this position?

The job title for this position is Applied Scientist 2/3.

What qualifications are required for this role?

A Ph.D. degree or Master’s degree in computer science, artificial intelligence, machine learning, operations research, or a related technical field is required, along with 5+ years of experience with a Master’s or 3+ years with a Ph.D.

Is prior experience in machine learning necessary?

Yes, applicants should have experience applying machine learning to solve real-world problems, as well as expertise in NLP, Transformers, and Large Language Models.

What programming languages and tools should candidates be proficient in?

Candidates should be proficient in Python or R and have experience with at least one deep learning library, such as PyTorch, TensorFlow, or Keras.

Are there specific types of models that the applicant should be familiar with?

Yes, familiarity with NLP, Transformers, Large Language Models, and optimization techniques around LLM training and serving is essential.

Will there be opportunities for involvement in the entire software lifecycle?

Yes, the role involves participating in the entire software lifecycle, including development, testing, continuous integration, and production operations.

What are the expectations regarding communication skills?

Candidates should be able to communicate technical ideas clearly, both verbally and in writing, including technical proposals, design specifications, and presentations.

Does Oracle have a commitment to diversity and inclusion?

Yes, Oracle is committed to expanding an inclusive workforce that promotes diverse insights and perspectives.

Are there opportunities for career growth within Oracle?

Yes, Oracle encourages constant learning and provides opportunities for employees to grow their careers and themselves.

What employee benefits does Oracle offer?

Oracle offers a highly competitive suite of employee benefits designed for work-life balance, flexible medical, life insurance, and retirement options.

Is there support for individuals with disabilities during the employment process?

Yes, Oracle is committed to including people with disabilities at all stages of the employment process and offers accessibility assistance if needed.

What types of machine learning solutions should candidates have experience in delivering?

Candidates should have experience delivering large-scale machine learning solutions for complex business problems and have a background in optimization and scaling of ML solutions.

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Oracle

Information Technology & Services

Technology
Industry
10,001+
Employees
1977
Founded Year

Mission & Purpose

We’re a cloud technology company that provides organizations around the world with computing infrastructure and software to help them innovate, unlock efficiencies and become more effective. We also created the world’s first – and only – autonomous database to help organize and secure our customers’ data. Oracle Cloud Infrastructure offers higher performance, security, and cost savings. It is designed so businesses can move workloads easily from on-premises systems to the cloud, and between cloud and on-premises and other clouds. Oracle Cloud applications provide business leaders with modern applications that help them innovate, attain sustainable growth, and become more resilient. The work we do is not only transforming the world of business--it's helping defend governments, and advance scientific and medical research. From nonprofits to companies of all sizes, millions of people use our tools to streamline supply chains, make HR more human, quickly pivot to a new financial plan, and connect data and people around the world. At work, we embrace diversity, encourage personal and professional growth, and celebrate a global team of passionate people developing innovative technologies that help people and companies tackle real-world problems head-on.