
Mastering Deep Models and Generative AI Systems
1 week ago
We are seeking a highly skilled senior engineer with expertise in machine learning, who can seamlessly blend knowledge of deep models with hands-on experience of generative AI systems.
Key Responsibilities:
- Design, fine-tune, and deploy large language model-based systems using advanced techniques such as prompt engineering, retrieval-augmented generation (RAG), and agent frameworks.
- Take ownership of the codebase: Deliver production-grade, reusable, and scalable code in Python and SQL, leveraging libraries like LangChain and LangGraph.
- Cloud deployment: Architect and optimize deployment pipelines on cloud platforms (Azure, AWS, or GCP), making sure CI/CD, scalability, and cost-efficiency are always considered.
- Collaborate across functions: Translate complex technical concepts into actionable insights for product owners, data scientists, and domain SMEs.
- Lead and mentor: Provide technical leadership, coach junior team members, and foster a culture of best practices in machine learning and LLM engineering.
- Stay ahead of the curve: Continuously experiment with new research, tools, and methods in generative AI to keep our solutions cutting-edge.
Requirements:
- 5+ years of professional experience in developing and deploying ML models in production environments.
- At least 1 year of practical experience working with large language models and generative AI, including prompt design, RAG pipelines, and AI agents.
- Proven ability to set and guide a technical roadmap for engineering teams.
- Advanced programming proficiency in Python and SQL with strong expertise in LangChain/LangGraph.
- Familiarity with cloud ecosystems (Azure, AWS, or GCP) and modern DevOps practices.
- Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders.
This is an exciting opportunity to join our organization and contribute to the development of innovative machine learning solutions.
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