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DIA Machine Lrng Eng at Ford Global Career Site

, , United States -

Full Time

Start Date

Immediate

Expiry Date

06 Feb, 26

Salary

0.0

Posted On

08 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Machine Learning, AI Technology, Data Visualization, MLOps, Data Engineering, Model Building, Generative AI, Statistical Techniques, Cloud-Based Deployments

Industry

Motor Vehicle Manufacturing

Description

Analyze source data and data flows, working with structured and unstructured data (text, audio, images, video, etc.) Apply AI and Machine Learning technology to solve complex, real-world problems Analyze and visualize diverse sources of data, interpret results in a business context and report results clearly and concisely Fulfill problem formulation and ML technique consulting requests in a timely manner Work collaboratively with different business partners and be able to present results in a clear and concise manner Established and active employee resource groups Experience with the complete software lifecycle Expertise in one or more core domains involved in machine learning model deployment, including data engineering, model building, MLOps Experience in productionizing generative AI to solve critical business problems Doctorate in computer science, mathematics, statistics, operations research, or related field AND 1+ year(s) data-science experience (e.g. managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's degree in computer science, mathematics, statistics, operations research, or related field AND 3+ year(s) data-science OR bachelor's degree in computer science, mathematics, statistics, operations research, or related field AND 5+ year(s) data-science experience Experience with cloud-based deployments and best practices

Responsibilities

Analyze source data and data flows, working with structured and unstructured data. Apply AI and Machine Learning technology to solve complex, real-world problems and report results clearly and concisely.