Artificial Intelligence Solutions Architect
1 day ago
About the Role
We are seeking an experienced Artificial Intelligence Solutions Architect to join our team at Ford Motor Company. In this role, you will be responsible for designing and implementing artificial intelligence and machine learning solutions.
The successful candidate will have a strong background in data science and experience with cloud-based platforms. They will be able to design, develop, and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
The ideal candidate will have a strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods. They will also have experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
In addition to technical skills, the candidate should have excellent problem-solving skills, analytical thinking, and the ability to communicate complex technical concepts effectively.
Key Responsibilities
- Design and implement AI/ML models and algorithms to solve complex business problems.
- Develop and maintain robust and efficient code using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Develop and maintain MLOps pipeline to monitor model performance in production and re-train as needed.
- Collaborate effectively with other engineers within the team.
- Ability to work within an agile development model working closely with a product manager and other engineers.
Required Skills and Qualifications
- Strong theoretical understanding of machine learning algorithms and techniques.
- Proven hands-on experience in developing and implementing AI/ML models using Python.
- Proficiency in using relevant libraries such as TensorFlow, PyTorch, scikit-learn, etc.
- Experience with data preprocessing, feature engineering, and model evaluation.
- Excellent problem-solving and analytical skills.
- Ability to work independently and as part of a team.
- Excellent communication and documentation skills.
Preferred Requirements
- Working knowledge of GCP.
- Expertise in open-sourcedata science technologies such as Python, R, Spark, SQL.
- Conceptual understanding of data pipelines and MLOps.
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