AI engineer
Salary & Market Data
Matched to BLS occupational data · Minnesota
Job Description
Job Overview We are seeking an experienced AI / Machine Learning Engineer to design, build, and deploy production-grade AI systems. In this role, you will bridge the gap between AI research and scalable software engineering. You will own the lifecycle of our AI features, from initial data curation and model selection to cloud deployment and continuous monitoring. Core Responsibilities
- Model Development : Design, train, and fine-tune machine learning models, including Large Language Models (LLMs) and predictive algorithms.
- System Architecture : Build robust, scalable, and secure data pipelines and AI infrastructures to support real-time inference.
- Production Deployment : Deploy models to cloud environments using modern MLOps practices, ensuring high availability and low latency.
- Optimization : Monitor system performance, optimize inference costs, and debug complex model behaviors in production.
- Collaboration : Work closely with Product Managers, Data Engineers, and Frontend developers to integrate AI features into user-facing products.
- Programming : Advanced proficiency in Python (knowledge of C++ or Go is a plus).
- Frameworks : Deep hands-on experience with PyTorch or TensorFlow.
- GenAI / LLM Stack : Proven experience with libraries like Hugging Face, LangChain, or LlamaIndex, and working with vector databases (e.g., Pinecone, Milvus, Qdrant).
- Data Engineering : Strong competency in SQL and experience handling large datasets using tools like pandas or Apache Spark.
- MLOps & Cloud : Hands-on experience with cloud providers (AWS, Google Cloud Platform, or Azure ) and containerization tools like Docker and Kubernetes .
- Education : Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Mathematics, or a highly quantitative field.
- Experience : 5+ years of software engineering experience, with at least 3+ years dedicated to building and deploying AI/ML models in a commercial production environment.
- Portfolio : A proven track record of shipping AI features that directly impacted business metrics or user experience.
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