Responsibilities
- Design, develop, and deploy AI/ML models for business and operational use cases
- Build and maintain data pipelines, model training workflows, and inference systems
- Work with structured and unstructured data (text, images, operational data)
- Integrate AI solutions into existing systems (ERP, internal tools, automation pipelines)
- Optimize models for performance, reliability, and cost efficiency
- Monitor, evaluate, and continuously improve deployed models
- Stay current with advancements in AI, ML, and applied intelligence
Basic qualifications
- Strong experience in Python and AI/ML frameworks (TensorFlow, PyTorch, or similar)
- Solid understanding of machine learning, deep learning, and data modeling
- Experience deploying models to production environments
- Familiarity with APIs, microservices, and system integration
- Ability to translate business problems into AI-driven solutions
- Strong analytical thinking and attention to detail
Preferred qualifications
- Experience with LLMs, NLP, or computer vision
- Experience integrating AI with ERP systems or operational platforms
- Knowledge of cloud platforms (AWS, GCP, or Azure)
- Experience with automation, agents, or decision-support systems
- Background in startup, product-driven, or innovation-focused environments
- Have you deployed AI/ML models into a production environment used by real users or business operations?
- Which tools or frameworks have you used professionally?
- How many years of hands-on experience do you have building and deploying AI or machine learning models?
- Can you describe a project where you integrated APIs for automation or AI chatbots?
Tags & focus areas
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