Machine Learning Engineer

Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. They are seeking a Machine Learning Engineer to build and scale business-facing AI agents, managing the entire lifecycle from prototype to production.

Why Join Us

• Ship production-grade AI systems that directly impact how users navigate their careers
• Own meaningful infrastructure decisions with real consequences at scale
• Operate at the intersection of ML research, systems engineering, and live product
• Help define the technical foundation of an AI-first job search experience

Responsibilities

• Architect and maintain the scalable infrastructure needed to reliably serve production AI agents at scale
• Build and continuously optimize LLM inference pipelines, with a focus on minimizing latency, maximizing throughput, and managing compute costs
• Develop automated monitoring, testing, and CI/CD workflows that keep our agents performant and production-ready
• Optimize data ingestion and processing pipelines to enable real-time agent responsiveness and support robust RAG architectures
• Design and maintain the APIs and backend services that connect AI model outputs to the user-facing product

Qualifications

Required

• Recent grad or early-career engineer (0–2 years) with a degree in Computer Science, Software Engineering, or a closely related field
• Strong Python skills and hands-on experience with backend frameworks such as FastAPI, Flask, or Django
• Working experience with ML frameworks like PyTorch or TensorFlow, paired with solid engineering fundamentals - version control, CI/CD, and unit testing
• Exposure to LLM deployment and a practical understanding of the infrastructure required to support autonomous agent systems
• Must be based in and authorized to work in the United States

Preferred

• Prior internship or project experience in MLOps, backend engineering, or distributed systems at an AI-focused company
• Hands-on familiarity with containerization tools (Docker, Kubernetes) and cloud platforms such as AWS, GCP, or Azure
• Experience working with vector databases - Pinecone, Milvus, Weaviate, or similar - in a production context
• Solid grasp of SQL and NoSQL database management for high-throughput, large-scale data workloads