AI Engineer – AI Agents

Job Description

Data Scientist, Early Career | Jobright.ai

The Tone:
This is an early career role at Jobright.ai, located in the United States. Jobright.ai is your personal AI job search agent, designed to transform the job search process into a fast, expert-guided journey. The company is seeking talent to build and scale business-facing AI agents, managing their entire lifecycle from prototype to production. This position is crucial for shaping how people experience AI-driven job search, offering the opportunity to build real, production AI agents that will be used by real users. You will benefit from high ownership and impact, working at the intersection of AI, agents, and product.

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 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 that 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 pipelines to improve agent performance and reliability.
• Data Analysis: Perform deep-dive statistical analysis on user interaction data to identify patterns that drive product improvements and feature innovation.
• Performance Monitoring: Monitor model performance and provide technical support during critical product iteration cycles.

The Must-Haves
• Background: This role is for a recent graduate or an entry-level professional with 0-2 years of experience. A degree in Data Science, Computer Science, Statistics, or a related quantitative field is required.
• Experience: Candidates must have 0-2 years of professional experience. A critical requirement for this position is that candidates must live in and be authorized to work in the United States.
• Skills: Strong programming proficiency in Python is essential, along with practical experience using machine learning libraries such as PyTorch, TensorFlow, or Scikit-learn. Candidates should possess a practical understanding of Large Language Model (LLM) architectures, prompt engineering techniques, and the evaluation methodologies for generative AI outputs. Excellent communication skills are also required, specifically the ability to articulate complex technical methodologies and modeling results effectively to the broader team.
• Bonus: Preferred qualifications include previous internship or research experience with a focus on Natural Language Processing (NLP), autonomous agents, or recommendation systems. Experience in building and maintaining data pipelines, as well as working with cloud infrastructure like AWS, GCP, or Azure, is a plus. A strong technical foundation in SQL and database management is also highly valued for efficient data extraction and feature engineering.