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Oracle Machine Learning Engineer: Audiences & Attributes in Broomfield, Colorado

Machine Learning Engineer: Audiences & Attributes

Preferred Qualifications

We are looking for a Machine Learning Engineer for the Audiences & Attributes Data Science team at Oracle Data Cloud, where we are leveraging the power of petabyte-scale data, technology, and data science to fuse offline sales with digital media. By helping clients and partners build, reach, and measure purchase-based audiences, ODC provides the core marketing infrastructure for a data-driven world. Our differentiator is the abundance of online and offline data available to build products and services for our clients in the digital advertising and marketing ecosystem.

The Audiences & Attributes Data Science team is powered by massive, signal-rich data sets, high engineering standards, and advanced data science. We use those tools to help our clients show the right ad to the right people at the right time and in the right place.

In the Machine Learning Engineer role, you'll collaborate with other team members, including data scientists, software engineers, product managers, and external partners to understand relevant business needs and optimize performance in our big data infrastructure. You will be combining traditional data science work and big data software engineering to build scalable, stable, cost-effective, repeatable, and accurate machine learning and graph-based ETL pipelines in the cloud. This work may span all aspects of data science and software development lifecycles. To be successful in this role, you must be equally an expert in machine learning and big data software engineering.

Role

  • develop and maintain production-quality ML systems, including ETL and on-demand modeling runtimes

  • provide thought leadership in the implementation of applied analytical solutions for business and end-user needs

  • collaborate with other developers (both data scientists and engineers) to design, research, implement, and integrate solutions

  • be a source of knowledge and mentorship for data scientists who don't have an engineering background

  • prototype and iteratively improve solutions based on provable, measurable value

  • build tools to help team members and stakeholders interact with and understand our data and modeling products

Prerequisites

  • MS or PhD in Computer Science, Mathematics, Physics, Engineering, Statistics, Econometrics, Operations Research, or equivalent industry experience

  • 3 years experience working on large-scale, production data processing systems including data ingestion, normalization, and storage

  • fluency in Scala

  • experience in Python or Java. Other languages are a plus.

  • understanding of ML model training and evaluation workflows; ability to assess, diagnose, and reason about a model's performance and suitability for various use cases

  • ability to apply core software engineering principles to practical business problems

  • experience developing Spark programs at scale, including tuning and debugging; experience with other distributed systems is a plus

  • experience with all aspects of VCS, CI/CD pipelines, and software build tools

  • experience instrumenting and monitoring data workflows in production

  • experience developing in cloud-native/container-based architecture (Kubernetes and its ecosystem)

  • experience with cloud computing environments (OCI, AWS, or comparable) and data storage solutions (Oracle, Exadata, Postgres, Elasticsearch, or comparable)

  • ability to automate the setup and management of data infrastructure

Detailed Description and Job Requirements

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.

Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

Job duties are varied and complex utilizing independent judgment. May have project lead role. 5 years relevant work experience. BS/BA preferred.

Oracle is an Affirmative Action-Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veterans status, age, or any other characteristic protected by law.

Job: Business Operations

Location: US-CO,Colorado-Broomfield

Job Type: Regular Employee Hire

Organization: Oracle

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