[Remote] Gen AI / Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Precision Technologies is a company that focuses on innovative technology solutions, and they are seeking a Gen AI / Machine Learning Engineer to design and develop AI-powered applications. The role involves building machine learning solutions, developing AI/ML APIs, and collaborating with various stakeholders to deliver effective AI-driven solutions.

Responsibilities

• Design, develop, and deploy Machine Learning and Generative AI solutions for business applications
• Build AI-powered applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models
• Fine-tune, evaluate, and optimize machine learning and foundation models
• Develop and deploy AI/ML APIs and microservices using Python frameworks such as FastAPI and Flask
• Build data pipelines for model training, inference, and monitoring
• Implement prompt engineering, model evaluation, and AI guardrails
• Integrate AI solutions with enterprise applications, cloud platforms, and external APIs
• Collaborate with Data Scientists, Software Engineers, Product Managers, and stakeholders to deliver AI-driven solutions
• Monitor model performance, scalability, reliability, and security in production environments
• Implement MLOps best practices, CI/CD automation, and model lifecycle management

Skills

• Design, develop, and deploy Machine Learning and Generative AI solutions for business applications
• Build AI-powered applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models
• Fine-tune, evaluate, and optimize machine learning and foundation models
• Develop and deploy AI/ML APIs and microservices using Python frameworks such as FastAPI and Flask
• Build data pipelines for model training, inference, and monitoring
• Implement prompt engineering, model evaluation, and AI guardrails
• Integrate AI solutions with enterprise applications, cloud platforms, and external APIs
• Collaborate with Data Scientists, Software Engineers, Product Managers, and stakeholders to deliver AI-driven solutions
• Monitor model performance, scalability, reliability, and security in production environments
• Implement MLOps best practices, CI/CD automation, and model lifecycle management

Company Overview