We are seeking a passionate and experienced Full Stack AI/ML Engineer with a strong background in machine learning and a drive for building intelligent systems. As a Full-Stack AI/ML Engineer on the Ford Pro Charging team, you will design, build, and ship intelligent services that power our global EV-charging platform. If you love turning data into real-world impact and thrive on end-to-end ownership from research notebooks to production APIs this is your playground.
Required Skills Qualifications:
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Experience:
2+ years of professional experience in Artificial Intelligence, Machine Learning, or Data Science roles, with a proven track record of delivering production-grade AI/ML solutions (or equivalent demonstrable expertise).
Technical Expertise:
- Proficiency in Python and strong experience with core AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers).
- Good understanding of Node.js backend development.
- Solid grasp of various machine learning algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures.
- Demonstrated experience applying machine learning to complex datasets, including structured and unstructured data.
- Proficient in API design (REST, GraphQL), microservices, and database design (SQL/NoSQL); production experience on at least one major cloud (AWS, Azure, or GCP).
- Practical knowledge of Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Argo, or similar).
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Problem-Solving:
Excellent analytical and problem-solving skills, with proven ability to break down complex problems into iterative experiments and devise effective, scalable AI/ML solutions -
Enthusiasm Learning:
A genuine passion for technology, coupled with a self-driven commitment to continuous learning and mastery of new techniques. We value individuals who proactively identify challenges, conceptualize solutions, and lead ideation and innovation, beyond mere task execution -
Communication:
Strong communication skills to articulate complex technical concepts to both technical and non-technical stakeholders. -
Education:
Bachelors or masters degree in computer science, Artificial Intelligence, Machine Learning, or a related quantitative field.
Bonus Points:
- Domain expertise in EV charging, smart-grid, or energy-management systems.
- Experience with distributed data technologies (Spark, Flink, Kafka Streams).
- Contributions to open-source ML projects or peer-reviewe'd publications.
- Knowledge of ethical and responsible AI frameworks, including bias detection and model explainability.
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Design Develop AI Solutions:
Lead the design, development, training, and evaluation of machine learning models and AI solutions across various domains to enhance our products and services. -
Identify AI Opportunities:
Proactively identify and explore opportunities to apply data-driven solutions to improve existing products, optimize internal processes, and create new value propositions. -
Model Implementation Optimization:
Implement, optimize, and deploy various machine learning algorithms and deep learning architectures to solve complex problems. -
Data Management Engineering:
Collaborate with data engineers to ensure robust data collection, preprocessing, feature engineering, and pipeline development for effective model training and performance. -
Backend Integration:
Design and implement robust APIs and services to integrate AI/ML models and solutions seamlessly into our existing backend infrastructure, ensuring scalability, reliability, and maintainability. -
Performance Monitoring Improvement:
Continuously monitor, evaluate, and fine-tune the performance, accuracy, and efficiency of deployed AI/ML models and systems. -
Research Innovation:
Stay abreast of the latest advancements in AI, ML, and relevant technologies, and propose innovative solutions to push the boundaries of our product capabilities. -
Testing Deployment:
Participate in the rigorous testing, deployment, and ongoing maintenance of AI/ML solutions in production environments.
