130 applicants

Company

Original Job Post

UPS · 6 days ago

Senior Machine Learning Engineer

Louisville, KY

Full-time

Onsite

Senior Level

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Responsibilities

Transforms and develops data science prototypes into ML systems using appropriate datasets and data representation models with moderate complexity.

Researches and implements appropriate ML algorithms and tools that create new systems and processes powered with ML and AI tools and techniques according to business requirements

Designs and implements workflows and analysis tools to streamline the development of new ML models at scale both in batch and streaming mode.

Creates and evolves ML models and software that enable state-of-the-art intelligent systems using best practices in all aspects of engineering and modeling lifecycles.

Extends existing ML libraries and frameworks with the developments in the Data Science and ML field for enterprise use.

Establishes, configures, and supports scalable cloud components that serve prediction model transactions

Integrates data from authoritative internal and external sources to form the foundation of a new Data Product that would deliver insights that supports business outcomes that is necessary for ML systems.

Collaborates with skilled Designers, Architects, Software Engineers, Data Scientists and Data Engineers to deliver ML products and systems for the organization.

Qualification

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Distributed-computingMachine-learningArtificial-intelligenceKerasPytorchScikit-learnCloud-ai-technologiesSolution-designBatch-processingStreaming-predictionModel-deploymentSoftware-scalabilityFeature-pipelineAgile-developmentCloud-technologyStatisticsForecastingTime-seriesHypothesis-testingClassificationRegression-analysisLinear-algebraBayesian-statisticsGroup-theoryProbabilityProblem-solvingHard-workingCollaborativeCommunicationCreative-thinking

Required

Experience designing and building large/data-intensive solutions using distributed computing within a multi-line business environment.

Knowledgeable in Machine Learning and Artificial Intelligence frameworks (i.e., Keras, PyTorch), libraries (i.e., scikit-learn), and tools and Cloud-AI technologies that aid in streamlining the development of machine learning or AI systems.

Strong experience in establishing and configuring scalable and cost-effective end-to-end solution design pattern components to support the serving of batch and live streaming prediction model transactions.

Experience in developing and implementing Machine Learning models such as: Classification/Regression Models, NLP models, and Deep Learning models; with a focus on productionizing those models into product features.

Experience deploying highly scalable software, scalable feature pipeline and model optimization that is supporting millions of transactions and/or a substantial number of users.

Experience in creating products and services that leverage best practices around software development lifecycle (SDLM), Agile development, and cloud technology.

Solid understanding of statistics such as forecasting, time series, hypothesis testing, classification, clustering, or regression analysis, and how to apply that knowledge in understanding and evaluating Machine Learning models.

Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory, and Probability.

Works collaboratively with management, and, in a technical and cross-functional context.

Strong written and verbal communication.

Possesses creative and critical thinking skills.

Bachelors’ (BS/BA) degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.

Preferred

Masters (MS/ME) degree in a quantitative discipline such as engineering, computer science, data science, bioinformatics, statistics, mathematics, international equivalent, or equivalent job experience.

Experience designing and building data-intensive solutions using distributed computing within a multi-line business environment.

Experience in establishing and configuring scalable and cost-effective end-to-end solution design pattern components to support the serving of batch and live streaming prediction model transactions in the Google Cloud Platform (GCP).

Experience with scalable data processing, feature development, and model optimization.

Knowledgeable in software development lifecycle (SDLM), Agile development practices, and cloud technology infrastructures and patterns related to product development.

Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory.

Works collaboratively, both in a technical and cross-functional context.

Prior experience within a UPS operational context (e.g., air gateways, hubs, ground facilities) that can aid with understanding business domain problems.