About the Company
Ford Motor Company is a global automotive leader renowned for its innovation and commitment to shaping the future of mobility. With a rich history spanning over a century, Ford is at the forefront of developing cutting-edge technologies, including advanced AI, machine learning, and autonomous driving systems. We empower our engineers to push boundaries, creating intelligent solutions that enhance safety, efficiency, and the overall driving experience for millions worldwide. Join a team where your contributions directly impact the evolution of the automotive industry.
Job Description
We are seeking a highly skilled and passionate Machine Learning Engineer to join our innovative AI/ML team at Ford Motor Company, located in Midtown, Detroit. This critical role is integral to developing, deploying, and maintaining advanced machine learning models across various facets of our business, from manufacturing optimization to customer experience and autonomous vehicle systems. You will work with large datasets, state-of-the-art algorithms, and robust MLOps practices to deliver impactful solutions. This position offers LMIA / Tier 2 Sponsorship, reflecting our commitment to attracting global talent. If you are a proactive problem-solver with a strong background in machine learning and a desire to make a significant impact in the automotive industry, we encourage you to apply.
Key Responsibilities
- Design, develop, and implement machine learning models and algorithms for various applications, including predictive maintenance, supply chain optimization, and in-car intelligence.
- Perform data preprocessing, feature engineering, and data analysis to prepare datasets for model training.
- Evaluate and optimize model performance, ensuring accuracy, scalability, and robustness.
- Collaborate with data scientists, software engineers, and product managers to integrate ML solutions into production systems.
- Develop and maintain MLOps pipelines for model deployment, monitoring, and retraining.
- Research and apply cutting-edge machine learning techniques and technologies.
- Contribute to the documentation of models, pipelines, and best practices.
- Participate in code reviews and foster a culture of technical excellence.
Required Skills
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of machine learning algorithms (e.g., deep learning, supervised/unsupervised learning, reinforcement learning).
- Experience with cloud platforms (e.g., AWS, Azure, GCP) for ML model deployment and management.
- Solid foundation in statistics, linear algebra, and calculus.
- Experience with data manipulation and analysis using SQL, Pandas, etc.
- Familiarity with MLOps principles and tools (e.g., Docker, Kubernetes, MLflow).
- Excellent problem-solving and communication skills.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
Preferred Qualifications
- Master's or Ph.D. in a relevant quantitative field.
- Experience with big data technologies (e.g., Spark, Hadoop).
- Knowledge of software engineering best practices (e.g., version control, CI/CD).
- Experience in the automotive industry or with large-scale IoT data.
- Familiarity with specific ML domains such as computer vision or natural language processing.
Perks & Benefits
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and holidays.
- 401(k) matching program.
- Employee vehicle purchase and lease programs.
- Professional development opportunities and tuition reimbursement.
- On-site fitness centers and wellness programs.
- Flexible work arrangements (where applicable).
- Access to cutting-edge technology and innovation labs.
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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