Data Scientist, Early Career
Jobright.ai · United States
- Hybrid
- Full-time
- $90,000 / year
- United States
Job highlights
- Build production AI agents from prototype to deployment.
- Optimize LLM prompts, fine-tuning, and RAG pipelines.
- Analyze user data for product improvements.
- Monitor model performance and provide support.
- Requires Python, ML libraries, and LLM understanding.
About the role
About Jobright.ai
Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. We are seeking an AI Engineer to build and scale business-facing AI agents, managing the entire lifecycle from prototype to production.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
- Develop and deploy predictive models and machine learning algorithms that power the core logic of our production AI agents
- Experiment with and optimize Large Language Model (LLM) prompts, fine-tuning techniques, and RAG pipelines to improve agent performance and reliability
- Perform deep-dive statistical analysis on user interaction data to identify patterns that drive product improvements and feature innovation
- Monitor model performance and provide technical support during critical product iteration cycles
Qualifications
Required
- 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
- Strong programming skills in Python and proficiency 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 with the ability to articulate technical methodology and complex modeling results to the broader team
- Must live in and be authorized to work in the United States
Preferred
- 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
Key skills/competency
- AI Engineer
- Machine Learning
- LLM
- Prompt Engineering
- Python
- PyTorch
- TensorFlow
- Scikit-learn
- Data Science
- NLP
Skills & topics
- AI Engineer
- Machine Learning
- LLM
- Python
- Data Science
- NLP
- Prompt Engineering
- Generative AI
- Software Engineer
- Entry Level
How to get hired
- Tailor your resume: Highlight Python, ML libraries (PyTorch, TensorFlow, Scikit-learn), LLM experience, and any NLP/agent projects.
- Showcase AI skills: Emphasize your understanding of LLM architectures, prompt engineering, and RAG pipelines in your application.
- Demonstrate quantitative ability: Detail your academic background in Data Science, CS, or Statistics and any relevant research experience.
- Prepare for technical interviews: Be ready to discuss ML concepts, Python coding, and how you'd approach building AI agents.
- Highlight US work authorization: Clearly state your ability to work in the United States.
Technical preparation
Master Python and essential ML libraries.,Practice LLM prompting and RAG techniques.,Build small AI agent prototypes.,Study statistical analysis and data interpretation.
Behavioral questions
Describe a challenging ML project you solved.,How do you handle complex modeling results?,Discuss your experience with LLM optimization.,Explain a time you improved product features.
Frequently asked questions
- What are the primary responsibilities of an AI Engineer at Jobright.ai?
- As an AI Engineer at Jobright.ai, you will develop and deploy machine learning models for AI agents, optimize LLM performance using techniques like prompt engineering and RAG, analyze user data to drive product innovation, and monitor model performance. You'll manage the AI agent lifecycle from prototype to production.
- What technical skills are required for the Early Career AI Engineer role at Jobright.ai?
- The role requires strong Python programming skills and proficiency with ML libraries such as PyTorch, TensorFlow, or Scikit-learn. A practical understanding of LLM architectures, prompt engineering, and generative AI evaluation is also essential. Familiarity with SQL and cloud platforms like AWS, GCP, or Azure is preferred.
- What qualifications does Jobright.ai look for in an Early Career AI Engineer?
- Jobright.ai seeks recent graduates or entry-level professionals (0-2 years experience) with a degree in Data Science, Computer Science, Statistics, or a related quantitative field. Excellent communication skills and the ability to articulate technical concepts are also required. Candidates must live in and be authorized to work in the United States.
- How does Jobright.ai's AI Engineer role offer high impact?
- The AI Engineer role at Jobright.ai offers high impact by enabling you to build and deploy real, production AI agents used by actual users. You'll work at the intersection of AI, agents, and product, directly shaping the AI-driven job search experience.
- What kind of projects can an AI Engineer expect to work on at Jobright.ai?
- You can expect to work on developing predictive models, optimizing LLM performance through prompt engineering and RAG, conducting statistical analysis on user data, and potentially contributing to autonomous agent development or recommendation systems, all within the context of an AI-driven job search platform.
- Is this an entry-level position at Jobright.ai?
- Yes, this is an Early Career AI Engineer position, suitable for recent graduates or professionals with 0-2 years of experience. The company is looking for individuals with a strong academic foundation and practical skills in AI and machine learning.
- What is the work arrangement for the AI Engineer position at Jobright.ai?
- The job description specifies that candidates must live in and be authorized to work in the United States, implying an on-site or hybrid arrangement within the US. Specific details on the work arrangement (on-site, hybrid, remote) would need further clarification from Jobright.ai.