
AI Engineer
2 days ago
We've all heard how crucial it is to set intentions, goals, and targets. Powerful goals electrify us. Clear intentions energize and pull us forward.
SHARE THIS:Key Responsibilities:
- Build and deploy AI models (LLMs, NLP, computer vision) using frameworks like TensorFlow, PyTorch, LangChain, and LangGraphs.
- Lead the development of Generative AI applications (text, image, or multimodal) using models like GPT, Gemini, Stable Diffusion, or custom architectures.
- Collaborate with data scientists, ML engineers, and product managers to translate business needs into AI solutions.
- Contribute to the architecture of AI infrastructure, including model serving and CI/CD for ML.
- Mentor junior developers and share best practices across the team.
- Develop APIs with Flask, FastAPI for model integration.
- Work with cross-functional teams to deliver AI-powered solutions.
- Utilize vector databases (e.g., Weaviate, Qdrant, FAISS, Chroma) for AI search and retrieval tasks.
Qualifications
- 2+ years of experience in Generative AI and deploying models using Flask, FastAPI.
- Strong proficiency in Python and libraries such as TensorFlow, PyTorch, LangChain.
- Proven track record of deploying AI/ML models in production.
- Familiarity with RESTful API principles and experience in API integration.
- Knowledge of embedding models and NLP pipelines.
- Experience with scraping and automation tools like Requests, Selenium, BeautifulSoup.
- Experience implementing RAG techniques in AI applications including chatbots.
- Experience with Computer Vision and Image Recognition models like YOLO, Facenet, Sadtalker, etc.
- Knowledge of transformers and LLMs (e.g., GPT, BERT, T5).
- Understanding of AI inference optimization and scalability.
- Experience with version control systems like Git.
- Expertise in ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
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