Machine Learning Engineer - GenAI & LLM Applicatoin

Full Stack Engineer - GenAI & LLM

Experience: 5 - 20 Years

Location: North America - Permanent Remote

Must-Have

• Experience with Microsoft OpenAI Azure or Google Vertex
• Experience developing GenAI applications (doesn't have to be professional)
• End-to-end full-stack application development
• Experience developing API endpoints in Python or Java
• Experience with PyTorch and/or TensorFlow
• Experience working with multiple AI Frameworks (hugging face, semantic search, RAG, etc)
  
  

Platform / Stack

You will work with technologies that include Microsoft OpenAI Azure, Google Vertex, PyTorch, and RAG Architecture.

What You'll Do As a Sr Software Engineer

• Architect, design, and develop AI applications, integrating with Google Vertex, Microsoft OpenAI Azure, and other LLM suites
• Design and implement effective prompts, configure LLM settings, and optimize performance through prompt crafting, RAG, fine-tuning and other techniques
• Collaborate with cross-functional teams to define requirements, manage user expectations, and deliver high-quality AI solutions
• Develop and maintain API endpoints, front-end features, and full-stack applications that leverage LLMs and Generative AI models
• Implement AI applications that comply with ethical guidelines and legal standards, particularly regarding data privacy and user consent
• Integrate analytics and monitoring tools to track user interactions, application performance, and the efficiency of LLM integrations
• Mentor, motivate, and develop the technical capabilities of the existing engineering team
• Stay up-to-date with emerging trends and advancements in Generative AI, LLMs, and related technologies
  
  

Qualifications

You could be a great fit if you have:

• 8+ years of experience in full-stack software development, with a strong focus on building enterprise-scale distributed and cloud or hybrid-cloud applications
• Regarded as an expert in the growing field of AI with 5+ years of experience developing AI solutions and prototypes, including Generative AI and LLMs
• Experience with PyTorch, TensorFlow, ONNX, LangChain, Kubernetes, and Docker
• Deep understanding of AI frameworks including Huggingface, semantic search, RAG, LLM agents, AgentGPT, orchestration, plugins, and LLM Ops
• Experience with Retrieval-Augmented Generation (RAG) architectures or frameworks like Langchain for building LLM-powered applications
• Proficiency in programming languages such as Python, Java, JavaScript, and experience with frameworks like React and Node.js
• Experience with cloud platforms such as Google Vertex, Microsoft OpenAI Azure, AWS, and Azure, using various solutions for developing integrations, APIs, and AI/ML applications
  
  

Skills: generative ai,llm agents,retrieval-augmented generation (rag),cloud platforms (google vertex, microsoft openai azure, aws, azure),microsoft openai azure,legal standards,pytorch,llm-powered applications,llm suites,java,ethical guidelines,google vertex,enterprise-scale distributed and cloud applications,kubernetes,node.js,distributed and cloud applications,agentgpt,semantic search,langchain,programming languages (python, java, javascript),distributed and cloud application development,api development,aws,azure,huggingface,genai applications,retrieval-augmented generation (rag) architectures,api endpoints in python,ai solutions and prototypes,analytics and monitoring tools,distributed and cloud,hybrid-cloud applications,orchestration,ai frameworks,plugins,full-stack software development,google,api endpoints,microsoft,tensorflow,api endpoints in java,llm integrations,ml applications,onnx,vertex,cloud,llm ops,react,llms,python,rag,full-stack application development,javascript,integrations,api,docker