AI Development Technical Specialist
7 days ago
Technical Specialist- ML Development
Area(s) of responsibilityJob Description
Key Responsibilities:
- Design, develop, and maintain scalable, efficient, and reliable systems to support GenAI and machine learning-based applications and use cases
- Lead the development of data pipelines, architectures, and tools to support data-intensive projects, ensuring high performance, security, and compliance
- Collaborate with other stakeholders to integrate AI and ML models into production-ready systems
- Work closely with non-backend expert counterparts, such as data scientists and ML engineers, to ensure seamless integration of AI and ML models into backend systems
- Ensure high-quality code, following best practices, and adhering to industry standards and company guidelines
Hard Requirements:
- Senior backend engineer with a proven track record of owning the backend portion of projects
- Experience collaborating with product, project, and domain team members
- Strong understanding of data pipelines, architectures, and tools
- Proficiency in Python (ability to read, write and debug Python code with minimal guidance)
Mandatory Skills:
- Machine Learning: experience with machine learning frameworks, such as scikit-learn, TensorFlow, or PyTorch
- Python: proficiency in Python programming, with experience working with libraries and frameworks, such as NumPy, pandas, and Flask
- Natural Language Processing: experience with NLP techniques, such as text processing, sentiment analysis, and topic modeling
- Deep Learning: experience with deep learning frameworks, such as TensorFlow, or PyTorch
- Data Science: experience working with data science tools
- Backend: experience with backend development, including design, development, and deployment of scalable and modular systems
- Artificial Intelligence: experience with AI concepts, including computer vision, robotics, and expert systems
- Pattern Recognition: experience with pattern recognition techniques, such as clustering, classification, and regression
- Statistical Modeling: experience with statistical modeling, including hypothesis testing, confidence intervals, and regression analysis
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