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Xerox Lead Machine Learning Engineer, AI in Palo Alto, California

Lead Machine Learning Engineer, AI

General information

City: Palo Alto

State/Province: California

Country: United States

Department: Research & Development

Date: Thursday, January 7, 2021

Working time: Full-time

Ref#: 20010204

Job Level: Manager without Direct Reports

Job Type: Experienced

Job Field: Research & Development

Description & Requirements

PARC, a Xerox company , is in the Business of Breakthroughs®. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. We create new business options, accelerate time to market, augment internal capabilities, and reduce risk for our clients. Since its inception, PARC has pioneered many technology platforms – from the Ethernet and laser printing to the GUI and ubiquitous computing – and has enabled the creation of many industries. Incorporated as an independent, wholly owned subsidiary of Xerox in 2002, PARC today continues the research that enables breakthroughs for our clients' businesses.

PARC AI is immediately hiring an experienced Machine Learning and AI Software Engineer to join our team in San Francisco. PARC AI has the vision of building a world class AI-as-a-Service platform to enable PARC’s customers to provision, deploy and manage PARC’s core AI solutions. The set of problems that we tackle is incredibly diverse and complex. They cut across Natural Language Processing (NLP), Computer Vision (CV), Augmented Reality (AR) and Conversational AI. We research and develop the algorithms and models that make our solution intelligent, as well as implementing, scaling, and maintaining the code that powers our production systems. You will participate in the entire research and development lifecycle, help to shape and refine requirements, own the design for your components, and write the code to implement important new capabilities we are adding to our product. The ideal candidate is a critical thinker, is passionate about solving mathematical and behavioral problems with data, and is excited about working in a fast-paced, innovative and collaborative environment.

Duties and Responsibilities:

  • Architect, design, implement and test machine learning product modules and new functionality according to requirements. This includes the analysis of large amounts of historical data, determining suitability for modeling, data clean-up and filtering, pattern identification and variable creation, selection of sampling criteria, generating performance definitions and variables, performing experiments with different types of algorithms and models, analyzing performance, to identify the best algorithms to employ.

  • Work with big data, crunching millions of samples for modeling data mining, recommendation, or behavioral change solutions

  • Design and develop machine learning enterprise and cloud product using a variety of languages/platforms to support integration and deployment of learning products and solutions

  • Champion and adhere to the Agile / SCRUM methodology.

  • Ensure Quality processes are followed throughout the development lifecycle.

  • Ensure adherence to Software Engineering best practices in development (Coding Standards, Unit Tests, Design Principles)

  • Perform design and code reviews and mentor less experienced developers.

  • Create Automated Unit Tests in a Test Driven development environment.

  • Work with on and offshore developers in a team focused environment, willingness to collaborate and communicate with others to solve a problem

  • Find and fix software defects.

  • Collaborate with Product Management to help envision and design new capabilities

  • Work with component technical lead(s) to write technical specifications for new features.

  • Partner with product managers, data scientists, engineers to execute and deliver team charter.

  • Work with engineers and data scientists to design and build generic ML model lifecycle management pipelines to create, deploy, monitor, upgrade, downgrade and deprecate ML models

  • Design and help implement data models and data pipelines that are scalable, re-usable and repeatable for the machine learning models with good understanding of PARC’s core solutions and the Life Science Domain.

  • Work with Data Scientists and ML Engineers to identify and select the best of breed ML frameworks, libraries and platforms to build ML models and solutions.

  • Work with Data Scientists and ML Engineers to design and implement reusable software components.

  • Work with Data Scientists to implement and test Prototype ML models

  • Work with ML Engineers to design and translate ML prototypes into production solutions that can serve multiple customers with minimum configuration and maximum automation.

  • Advice/Document best practices with respect to data partitioning, data storage, system performance monitoring/tuning, memory management, model scalability, model performance monitoring/tuning and data quality monitoring/tuning.

Required Experience and Skills:

  • MS/PhD degree in Computer Sciences or Engineering or Data Science.

  • Relevant experience with a proven track record of developing algorithms and machine learning products for production ready recommendation or prediction systems using languages and big data platforms such as Scala, Python, R, Java and Spark.

  • Aptitude to quickly learn, understand and abstract complex data models

  • Strong scripting skills in Python/Groovy/Shell

  • Experience with machine learning tools and how to build efficient end-to-end ML workflow (e.g. Scikit, Numpy, Pandas, MLflow)

  • Experience with at least one Deep Learning framework such as TensorFlow, Keras or PyToch

  • 4+ years of industry experience developing ML models, with AR/CV/NLP preferred

  • Deep understanding in several NLP areas such as classification, named-entity recognition, POS tagging, word embeddings

  • In depth understanding and appreciation of continuous delivery, cloud platforms (AWS), observability, infrastructure as code, configuration management, containers, operations and automation

  • High-energy self-starter with a passion for your work


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