Request ID: 97881-1
Title: Machine Learning Engineer
Locations: Sunrise, FL
Duration: 06+ Months with Possible Extension.
Pay Range: $45-$47/Hour on W2/ C2C (All inclusive)
We are seeking an experienced Senior Generative AI / Machine Learning Engineer to design, develop, and deploy production-ready Generative AI solutions powered by Large Language Models (LLMs). The ideal candidate will have strong hands-on experience with Python, LLMs, LangChain, LangGraph, agentic AI workflows, LLM memory, retrieval pipelines, and machine learning engineering.
The candidate will work across the complete AI/ML lifecycle, including model evaluation and selection, solution design, development, deployment, monitoring, and optimization of scalable GenAI applications.
Key Responsibilities
- Design, develop, and productionize Generative AI applications using open-source and proprietary LLMs.
- Evaluate and integrate LLMs such as OpenAI, Anthropic, Llama, and Mistral based on business and technical requirements.
- Design and implement agentic AI workflows using LangChain and LangGraph.
- Develop multi-step AI orchestration workflows for complex business use cases.
- Implement short-term and long-term memory strategies for LLM-based applications.
- Design and manage state management and context-handling mechanisms for agentic systems.
- Optimize prompts, retrieval pipelines, context management, and orchestration logic.
- Develop and integrate RAG/retrieval-based solutions for enterprise GenAI applications.
- Develop machine learning models and production-ready AI/ML solutions where required.
- Build scalable and reliable AI services using Python and ML engineering best practices.
- Deploy, monitor, troubleshoot, and maintain AI/ML and GenAI systems in production environments.
- Collaborate with product, platform, data science, engineering, and business teams to deliver scalable AI solutions.
- Establish appropriate evaluation strategies to measure model quality, accuracy, performance, and reliability.
- Continuously research and evaluate emerging LLM, GenAI, and agentic AI technologies.
Required Skills
- 8 9 years of experience in Machine Learning, AI Engineering, Data Science, or related fields.
- Strong hands-on experience developing Generative AI and LLM-based applications.
- Strong experience with LLMs including OpenAI, Anthropic, Llama, Mistral, or comparable models.
- Hands-on experience with LangChain and/or LangGraph.
- Strong understanding of agentic AI architectures and workflows.
- Solid understanding of LLM memory architecture, state management, and context handling.
- Strong proficiency in Python.
- Experience with prompt engineering and optimization.
- Experience designing and optimizing retrieval/RAG pipelines.
- Strong understanding of machine learning concepts and ML engineering best practices.
- Experience deploying and supporting production-grade AI/ML systems.
- Strong analytical, troubleshooting, and problem-solving skills.
Nice-to-Have Skills
- Experience with Google Cloud Platform (GCP).
- Hands-on experience with Vertex AI, BigQuery, and Google Cloud Storage (GCS).
- Experience building and deploying ML models.
- Experience with MLOps and production model lifecycle management.
- Experience with model evaluation, monitoring, and observability.
- Experience with enterprise-scale GenAI implementations.
- Experience working with open-source LLM frameworks and models.
Roles & Responsibilities
- Lead end-to-end development of GenAI solutions from model selection through production deployment.
- Build agentic applications using LangChain/LangGraph.
- Implement memory and state management capabilities for LLM applications.
- Develop and optimize prompts, retrieval mechanisms, and AI orchestration workflows.
- Build ML models and integrate them into production AI solutions.
- Deploy and maintain scalable AI/ML applications.
- Monitor model and application performance and troubleshoot production issues.
- Collaborate with product and platform teams to translate business requirements into AI solutions.
- Evaluate new LLMs and GenAI technologies and recommend appropriate solutions.