AI Engineer – AI Agents

Job Description

Data Scientist, Early Career | Jobright.ai

The Tone:
This is a full-time role at Jobright.ai, located remotely within the United States. Jobright is your personal AI job search agent, dedicated to transforming the job search process into a fast, expert-guided journey for users. This position is crucial for building and scaling business-facing AI agents, taking them through their entire lifecycle from initial prototype to full production deployment. You will play a significant part in shaping how people interact with and experience AI-driven job search solutions, directly impacting our users and product direction.

The TL;DR
• Role: Early Career
• Location: United States
• Mission: Own the development and deployment of predictive models and machine learning algorithms that power Jobright’s core production AI agents.
• Tech Stack: Python, PyTorch, TensorFlow, Scikit-learn, SQL, AWS, GCP, Azure

What You’ll Actually Do
• Model Development: Develop and deploy predictive models and machine learning algorithms to power the core logic of our production AI agents.
• LLM Optimization: Experiment with and optimize Large Language Model (LLM) prompts, fine-tuning techniques, and RAG (Retrieval Augmented Generation) pipelines to continuously improve agent performance and reliability.
• Data Analysis: Perform deep-dive statistical analysis on user interaction data to identify critical patterns that drive product improvements and inform future feature innovation.
• Performance Monitoring: Monitor the performance of deployed models and provide essential technical support during critical product iteration cycles to ensure stability and effectiveness.

The Must-Haves
• Background: Recent graduate or entry-level professional (0–2 years of experience) with a degree in Data Science, Computer Science, Statistics, or a related quantitative field. Must live in and be authorized to work in the United States.
• Experience: 0–2 years of professional experience.
• Skills: Strong programming proficiency in Python and hands-on experience with machine learning libraries such as PyTorch, TensorFlow, or Scikit-learn. Practical understanding of LLM architectures, prompt engineering, and the evaluation of generative AI outputs. Excellent communication skills are required to articulate technical methodology and complex modeling results to the broader team.
• Bonus: Previous internship or research experience specifically focused on Natural Language Processing (NLP), autonomous agents, or recommendation systems. Experience building and maintaining data pipelines. Familiarity with cloud infrastructure (AWS/GCP/Azure). Strong technical foundation in SQL and database management for efficient data extraction and feature engineering.