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3 days ago
We are seeking a seasoned professional to lead the development and integration of Python-based applications with Large Language Models (LLMs).
- The ideal candidate will have experience architecting and implementing LLM pipelines, including prompt engineering, retrieval-augmented generation, fine-tuning, and evaluation.
- They will design scalable microservices and APIs for AI features, collaborate with MLOps teams to deploy and monitor AI models in production, and ensure performance optimization, cost efficiency, and security in LLM workflows.
- A strong leader, they will guide the team on Python best practices, code reviews, and technical problem-solving, while staying updated on emerging AI/LLM advancements and proposing adoption where beneficial.
To excel in this role, candidates must possess:
- Strong proficiency in Python, FastAPI, and Flask.
- Solid experience with LLM integration, OpenAI API, Hugging Face Transformers, LangChain, and LlamaIndex.
- Understanding of Retrieval-Augmented Generation (RAG) pipelines, vector databases like Pinecone, Weaviate, FAISS, and Milvus.
- Experience with prompt engineering & evaluation techniques. Knowledge of MLOps tools, MLflow, Kubeflow, and deployment on AWS/GCP/Azure.
- Familiarity with containerization and orchestration, Docker, and Kubernetes.
- Strong grasp of REST APIs, GraphQL, and microservices architecture. Knowledge of model fine-tuning and performance optimization.
This is an excellent opportunity for experienced professionals looking to grow their careers in AI and LLM development. Our team offers:
- Collaborative environment that fosters innovation and growth.
- Opportunities for professional development and mentorship.
- Competitive compensation and benefits package.
We strive to provide a dynamic and supportive work environment that allows our employees to thrive. If you are a skilled professional looking to make a meaningful contribution to our team, please submit your application.
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