Description

Job Description

This role is embedded with Ford Performance, Ford's motorsport division, for the first two years. Successful candidates will be expected to develop AI and Machine Learning-driven solutions for Ford Performance and its motorsport partners. They will leverage diverse sources of data, such as time-series, images, audio, and video to develop predictive models and deploy them in prototype applications for downstream consumption. Frequent travel will be required.

Responsibilities

• Analyze source data and data flows, working with structured and unstructured data (text, audio, images, video, etc.)
• Manipulate high-volume, high-dimensionality data from varying sources to expose and highlight patterns, anomalies, relationships, and trends.
• Apply AI and Machine Learning technology to solve complex, real-world problems.
• Analyze and visualize diverse sources of data, interpret results and report results clearly and concisely.
• Fulfill problem formulation and ML approaches.

Qualifications

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Statistics, Applied mathematics, or other engineering discipline.
• 2-3+ years experience in feature engineering, model development, hyper parameter tuning, and model evaluation
• 2-3+ years experience with Python, Pandas/Numpy/ScikitLearn, Pytorch, Tensorflow, Huggingface
• 2+ years Google Cloud Platform
• Core concepts of modern NLP or Computer Vision modeling techniques
• Familiarity with best practices in deep learning
• Familiarity with API and application development and tools such as FastAPI or Dash.
• Strong technical writing and oral skills

Preferred Qualifications:

• Ph.D. degree in a STEM field
• Git and best practices in GitHub
• Test and Behavior Driven Development
• OS: Linux shell scripts and Docker containers
• Exposure to best practices in CI/CD

*Travel is required for the first 2 years in this role due to client demand, once a month expected*

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:

• Immediate medical, dental, and prescription drug coverage

• Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more

• Vehicle discount program for employees and family members, and management leases

• Tuition assistance

• Established and active employee resource groups

• Paid time off for individual and team community service

• A generous schedule of paid holidays, including the week between Christmas and New Year's Day

• Paid time off and the option to purchase additional vacation time.

For a detailed look at our benefits, click here: Benefit Summary

This role is based out of Palo Alto, CA or Dearborn, MI, you will be required to be on-site 4 days/week.

*Visa Sponsorship IS provided for this specific role*

*Relocation assistance IS provided for this specific role*

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, If you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

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