Machine Learning Engineer

"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"
• 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 Role Descriptions: 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 HaveExperience with GCP services (e.g.| Vertex AI| BigQuery| GCS).Experience deploying ML/GenAI systems in production environments.data scientistCan do ML modelRoles & ResponsibilitiesDesign| 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.
Essential Skills: 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 HaveExperience with GCP services (e.g.| Vertex AI| BigQuery| GCS).Experience deploying ML/GenAI systems in production environments.data scientistCan do ML modelRoles & ResponsibilitiesDesign| 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.
Desirable Skills:
Keyword:
Skills: Digital : Machine Learning
Experience Required: