Machine Learning Engineer

Role: Machine Learning Engineer

Location: Sunrise, FL - onsite

Duration: 6+ months

Rate: $62/hr

"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

Generative AI & LLMs LangChain / LangGraph ML model

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.

Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.