> Markdown version of [/jobs/ext/543420-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/543420-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** WAVERLEY SOFTWARE, INC. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, System Configuration, Continuous Integration, Information Engineering, Github, Python (Programming Language), Machine Learning, Open Source Technology, Software Tools, Tensorflow, Search Technologies, Software Engineering, Systems Integration, Google Cloud, Data Ingestion, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Model Validation, AI Platforms, HuggingFace, Machine Learning Operations, Software Coding, Software Version Control, Data Pipelines - **Published:** June 10, 2026 - **Apply:** https://waverleysoftware.com/careers/ai-ml-engineer ## About the Role * 5+ years of professional Machine Learning or Data Engineering experience, featuring deep expertise and strong coding skills in Python. * Production experience with ML frameworks (PyTorch, TensorFlow) and comprehensive knowledge of LLM ecosystems (OpenAI, Hugging Face Transformers, LangChain). * Hands-on experience building and deploying RAG pipelines and managing Vector Databases (Pinecone, Milvus, Weaviate, Qdrant, or pgvector). * Experience with cloud platforms (AWS, GCP, Azure). * Knowledge of data engineering tools (such as Apache Airflow and Spark). * Understanding of MLOps and collaborative development, including model versioning, monitoring, GitHub, and CI/CD practices. * Experience with system integrations and orchestration. * Strong communication skills, with the ability to articulate complex data science concepts and architectural trade-offs to client-side technical leadership (CTOs, Lead Data Scientists)., * Experience with open-source model deployment (Llama 3, Mistral) and fine-tuning techniques. * Familiarity with managed cloud AI services (AWS SageMaker, Vertex AI, or Azure AI). ## Description We are looking for a Senior AI/ML Engineer. You will serve as the core data and machine-learning authority during client engagements, proposing advanced AI architectures and data pipelines. In the delivery phase, you will be hands-on, writing the heavy Python code required to implement RAG systems, configure vector databases, and fine-tune machine learning models., * Architecture & Proposals: Consult with clients to assess their data readiness, recommend optimal ML approaches (e.g., prompt engineering vs. fine-tuning), and design scalable AI architectures. * Hands-On AI Development: Build and optimize complex RAG architectures, multi-agent systems, and semantic search capabilities. * Data Engineering: Design data ingestion, chunking, and embedding pipelines to feed intelligence into the applications. * Model Management & Evaluation: Handle model selection, parameter-efficient fine-tuning (PEFT/LoRA), and deployment configuration. Continuously evaluate model performance and iterate based on metrics. * Production Reliability & Monitoring: Ensure ongoing model scalability, reliability, and robust monitoring in production environments. * Performance & Cost Optimization: Proactively identify and implement strategies to optimize both the computational performance and operational costs of AI systems. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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