drjobs Machine Learning Engineer

Machine Learning Engineer

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1 Vacancy
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Job Location drjobs

Dearborn, MI - USA

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Description

We are seeking an experienced Machine Learning Engineer to design implement and maintain robust analytics pipeline solutions. These solutions will support the analysis modeling and prediction of upstream and downstream auction prices directly benefiting the Business and Sales Planning Analytics (BSPA) Used Vehicle Analytics team and its customers. The ideal candidate will excel at developing ML/Software Engineering Solutions performing DevSecOps and collaborating with crossfunctional teams (including ML Engineers Data Scientists and Data Engineers) to improve processes and drive business performance.



Responsibilities

Responsibilities:

  • Develop build and maintain infrastructure required for machine learning including data pipelines model deployment platforms and model monitoring.
  • Develop and maintain tools and libraries to support the development and deployment of machine learning models.
  • Automate machine learning workflows using DevSecOps principles and practices.
  • Collaborate with development and operations teams to implement software solutions that improve system integration and automation of ML pipelines.
  • Design develop and manage data flows and APIs between upstream systems and applications.
  • Troubleshoot and resolve issues related to system communication data flow and data quality.
  • Create and maintain comprehensive technical documentation of software components.
  • Implement and enforce the highest standards of data quality and integrity across all data processes.
  • Manage deliverables through project management tools.
  • Collaborate with technical and nontechnical teams to gather integration requirements and ensure successful deployment of data solutions.
  • Work with IT to ensure systems meet evolving business needs and comply with data governance policies and security requirements.


Qualifications

Minimum Qualifications:

  • Bachelors degree in Computer Science Information Systems or a related field.
  • 3 years of experience in developing and deploying machine learning models in a production environment.
  • 3 years of experience in programming with Python
  • 2 years of handson experience utilizing Google Cloud Platform (GCP) services including BigQuery and Google Cloud Storage to efficiently manage and process large datasets as well as Cloud Composer and/or Cloud Run.
  • Experience with version control systems like GitHub for managing code repositories and collaboration.
  • 2 years of experience with code quality and security scanning tools such as SonarQube Cycode and FOSSA.
  • 3 years of experience with data engineering tools and technologies such as Kubernetes ContainerasaService (CaaS) platforms OpenShift DataProc Spark (with PySpark) or Airflow.
  • Experience with CI/CD practices and tools including Tekton or Terraform as well as containerization technologies like Docker or Kubernetes.
  • Excellent problemsolving and analytical skills with a focus on datadriven solutions.
  • Familiarity with cloud computing platforms like AWS Azure or Google Cloud Platform.
  • Familiarity with Atlassian project management tools (e.g. Jira Confluence) and agile practices.

Preferred Qualifications:

  • 5 years of experience in the automotive industry particularly in auto remarketing and sales.
  • Masters degree in a relevant field (e.g. Computer Science Data Science Engineering).
  • Proven ability to thrive in dynamic environments managing multiple priorities and delivering highimpact results even with limited information.
  • Exceptional problemsolving skills a proactive and strategic mindset and a passion for technical excellence and innovation in data engineering.
  • Demonstrated commitment to continuous learning and professional development.
  • Familiarity with machine learning libraries such as TensorFlow PyTorch or Scikitlearn
  • Experience with MLOps tools and platforms.

You may not check every box or your experience may look a little different from what weve 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 builderor 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 rampup programs subsidized backup 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 Years Day

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

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

*Please note: This is a hybrid role based in Dearborn MI you are expected to commute onsite up to 3 times a week*

*Visa Sponsorship is NOT provided for this 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.

#LIHybrid

#LIDS2



Employment Type

Full-Time

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