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AI Engineer
2 weeks ago
Responsibilities:
- Design, build, and deploy AI/ML models using frameworks such as PyTorch, scikit-learn, or Hugging Face Transformers.
- Develop and maintain Python-based applications for AI solutions.
- Work on Generative AI (GenAI) projects including LLM fine-tuning, prompt engineering, and integration into products.
- Implement, train, and optimize models for NLP, computer vision, and predictive analytics use cases.
- Build and orchestrate AI workflows using LangChain and LangGraph for LLM applications.
- Deploy models into production environments, ensuring scalability and performance.
- Collaborate with cross-functional teams to design AI-powered system features and integrations.
- Develop APIs and services to serve AI/ML models in real-time applications.
- Troubleshoot, debug, and continuously improve AI models and pipelines.
- Stay up to date with advancements in AI/ML, GenAI, and emerging technologies.
Requirements:
- 2-4 years of hands-on experience in AI/ML engineering.
- Strong proficiency in Python with experience in AI/ML model development.
- Practical experience with ML frameworks such as PyTorch, scikit-learn, and Hugging Face Transformers.
- Exposure to Generative AI (LLMs, embeddings, prompt engineering, and vector databases).
- Hands-on experience with LangChain and LangGraph for building agentic AI workflows.
- Experience in NLP, computer vision, or predictive analytics projects.
- Solid understanding of model deployment via REST APIs (FastAPI/Flask).
- Familiarity with cloud platforms (AWS, Azure, or GCP) for AI/ML deployment.
- Experience with Git version control and CI/CD practices.
- Knowledge of Docker/Kubernetes for containerized AI deployments (preferred).
- Strong problem-solving skills and ability to work in collaborative environments.