Machine Learning Engineer - Early Career
2 - 5 years
United States
Full-time
Remote
1 month ago
About the role
Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. They are seeking an AI Engineer to build and scale business-facing AI agents, managing the entire lifecycle from prototype to production.
Why Join Us
Responsibilities
Qualification
Required
Preferred
Why Join Us
- Build real, production AI agents used by real users
- High ownership and impact
- Work at the intersection of AI, agents, and product
- Shape how people experience AI-driven job search
Responsibilities
- Design, build, and maintain the scalable infrastructure required to deploy and serve production-grade AI agents
- Implement and optimize Large Language Model (LLM) pipelines, focusing on latency reduction, throughput, and efficient resource utilization
- Develop automated systems for model monitoring, testing, and continuous integration to ensure the reliability of our AI agents
- Optimize data ingestion and processing layers to support real-time agent responsiveness and complex RAG (Retrieval-Augmented Generation) architectures
- Architect and refine APIs and backend services that bridge the gap between AI models and the user-facing product
Qualification
Required
- Recent graduate or early-career professional (0–2 years of experience) with a degree in Computer Science, Software Engineering, or a related technical field
- Strong proficiency in Python and experience with backend frameworks (such as FastAPI, Flask, or Django)
- Practical experience with machine learning frameworks (PyTorch or TensorFlow) and a solid understanding of software engineering best practices (version control, CI/CD, unit testing)
- Familiarity with the deployment of LLMs and an understanding of the infrastructure required to support autonomous agents
- Must live in and be authorized to work in the United States
Preferred
- Previous internship or project experience in ML Ops, backend engineering, or distributed systems within an AI-focused company
- Hands-on experience with containerization (Docker, Kubernetes) and cloud infrastructure (AWS, GCP, or Azure)
- Knowledge of vector databases (such as Pinecone, Milvus, or Weaviate) and their role in production AI systems
- Strong foundation in SQL and NoSQL database management for high-scale data handling
Skills
EngineeringSoftware Development