Machine Learning Engineer
Indexed description
Role :: Machine Learning Engineer
Location :: Sunrise, FL
Type :: Fulltime
Experience Required -8+ Years
(Generative AI & LLMs LangChain / LangGraph ML model)
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
Must Have Technical/Functional Skills:
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
- Implement short-term and long-term memory strategies for LLM-based systems.
- Optimize prompts, retrieval pipelines, and orchestration logic.
- Collaborate with product and platform teams to deliver scalable AI solutions.
Required Qualifications
- Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral)
- Hands-on experience with LangChain and/or LangGraph.
- Solid understanding of LLM memory architecture and state management.
- Proficiency in Python and ML engineering best practices.
Nice to Have
- Experience with GCP services (e.g., Vertex AI, BigQuery, GCS).
- Experience deploying ML/GenAI systems in production environments.
- data scientist
- Can do ML model
Roles & Responsibilities
- Design, develop, and deploy GenAI applications using LLMs.
- Build and implement agentic workflows using LangChain/LangGraph.
- Develop ML models and production-ready AI solutions.
- Implement and manage LLM memory and state management strategies.
- Optimize prompts, retrieval pipelines, and orchestration workflows.
- Collaborate with product and platform teams to deliver scalable AI solutions.
- Deploy, monitor, and maintain AI/ML systems in production environments.
- Evaluate and integrate open-source and proprietary LLMs.
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