AI Engineer

Job Description

Data Scientist, Early Career | Jobright.ai

The Tone:
This is a full-time role at Jobright.ai, located in the United States. Jobright.ai is your personal AI job search agent that aims to transform the job search process into a fast, expert-guided journey. This role is crucial for developing and scaling business-facing AI agents, directly impacting how users experience AI-driven job search and enhancing the core product’s intelligence and reliability.

The TL;DR
• Role: Early Career
• Type: Full-time
• Location: Remote, United States

• Mission: Develop and optimize the predictive models and LLM-powered logic that drive the company’s core AI agents.
• Tech Stack: Python, PyTorch, TensorFlow, Scikit-learn, SQL, AWS/GCP/Azure

What You’ll Actually Do
• Develop: Develop and deploy predictive models and machine learning algorithms that power the core logic of our production AI agents.
• Experiment: Experiment with and optimize Large Language Model (LLM) prompts, fine-tuning techniques, and RAG pipelines to improve agent performance and reliability.
• Analyze: Perform deep-dive statistical analysis on user interaction data to identify patterns that drive product improvements and feature innovation.
• Monitor: Monitor model performance and provide technical support during critical product iteration cycles.

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.
• Experience: 0-2 years of experience in data science, machine learning, or related quantitative roles, with a practical understanding of LLM architectures, prompt engineering, and the evaluation of generative AI outputs.
• Skills: Strong programming skills in Python, proficiency with machine learning libraries such as PyTorch, TensorFlow, or Scikit-learn, and excellent communication skills.
• Bonus: Previous internship or research experience focused on Natural Language Processing (NLP), autonomous agents, or recommendation systems; experience building and maintaining data pipelines and working with cloud infrastructure (AWS/GCP/Azure); strong technical foundation in SQL and database management for efficient data extraction and feature engineering.