What are the responsibilities and job description for the AI/ML Engineer position at Stefanini North America and APAC?
Job Description
This role will involve the development and maintenance of applications that can ingest data from multiple engineering systems in the backend and provide an AI/ML enabled web front end to provide predictive analytics, automation, and engineering insights.
Experience Required
- At least 5 years of experience in Data Engineering with a focus on full stack development.
- Proven experience in developing applications with integrated AI/ML features.
- Work with databases for data storage, retrieval, and management tailored to AI/ML needs.
- Strong experience with ETL processes (e.g., using tools like Apache Kafka, Talend, or custom scripts).
- Knowledge of various database systems (SQL, NoSQL like MongoDB, Cassandra).
- Experience with data warehousing concepts and tools (e.g. Google BigQuery).
- Incorporate machine learning models into our applications to enhance functionality, including but not limited to natural language processing, image recognition, and predictive analytics.
- Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn for model development.
- Knowledge of chatbot development platforms like Dialogflow.
- Knowledge of frameworks like LangChain and Retrieval Augmented Generation (RAG).
- Design, develop, and maintain scalable and efficient web applications using modern frameworks (e.g., React, Angular for frontend; Node.js, Django for backend).
- Proficiency in at least one major cloud platform (Google Cloud preferred) for data storage, processing, and hosting AI services.
- Develop RESTful APIs to ensure seamless integration between frontend, backend, and external services.
- Basic understanding of CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
- Continuously improve application performance through code refactoring, optimization of data pipelines, and tuning of machine learning models.
Education Required
- Bachelors/Masters degree in computer science, Information Technology, or related fields with a special focus on Data Engineering and AI/ML.
Education Preferred
- Certifications in AI/ML like Google's Professional Machine Learning Engineer are optional but beneficial.
