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- Tasks: Join us as a Research Assistant to prototype and test cutting-edge AI agents.
- Company: US Tech Solutions is a global leader in talent solutions, connecting you with exciting opportunities.
- Benefits: Enjoy flexible work options and the chance to work on innovative projects in AI.
- Why this job: Be at the forefront of AI technology, making a real impact while developing your skills.
- Qualifications: You need a degree in Computer Science and 2+ years in AI prototyping or research.
- Other info: This role has potential for extension beyond the initial 3-month period.
Research Assistant – AI Agents & LLM Prototyping
Overview
We are looking for a Research Assistant with 2+ years of experience in prototyping and testing AI agents or large language models (LLMs). You will design test prompts, experiment with prompt engineering, and debug AI agent tool calls within a Python/PHP software stack. You’ll also help create internal benchmarks to evaluate AI agent performance.
Duration: 03-month (Likely extension)
Key Responsibilities
- Create and refine test prompts to guide AI agents toward desired behavior.
- Implement and troubleshoot AI agent tool calls in a Python/PHP environment.
- Develop high-quality prompts to build internal evaluation benchmarks for AI agents.
- Test AI agents to assess their ability to perform tasks such as ordering, scheduling, or cancelling meetings.
- Analyze test outcomes, identify issues, and communicate findings for continuous improvement.
- Navigate and understand the Python codebase to correlate test results with underlying code.
- Improve and test existing AI agents.
- Identify where agents perform well and where they fail.
- Prompt testing and tuning to optimize agent responses.
- Flagging test results as pass/fail based on expected behavior.
Technical Skills & Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
- 2+ years of experience in research or prototyping within machine learning, deep learning, or natural language processing.
- Proficient in Python, with the ability to understand and work with a codebase containing multiple interrelated files.
- Experience with AI agent frameworks such as Model Context Protocol (MCP) and LangChain.
- Familiarity with architectural patterns of large-scale software systems.
- Basic knowledge of SQL and data analysis is a plus.
- Experience using source control systems (e.g., Git).
- Experience in generative AI and LLM research preferred.
- Python programming
- Generative AI knowledge
- Understanding of MCP servers and LangChain frameworks
About US Tech Solutions
US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com.
US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Recruiter Details
Email: ajit.kumar@ustechsolutionsinc.com
Job details
- Seniority level: Associate
- Employment type: Contract
- Job function: Research
- Industries: Software Development
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Research Assistant – AI Agents & LLM Prototyping employer: US Tech Solutions
Contact Detail:
US Tech Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Assistant – AI Agents & LLM Prototyping
✨Tip Number 1
Familiarise yourself with the latest advancements in AI agents and large language models. Being well-versed in current trends and technologies will not only boost your confidence during discussions but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with online communities or forums related to AI and machine learning. Networking with professionals in these spaces can provide valuable insights and potentially lead to referrals, which can significantly enhance your chances of landing the job.
✨Tip Number 3
Prepare to discuss specific projects where you've implemented prompt engineering or worked with AI agents. Having concrete examples ready will help you illustrate your experience and problem-solving skills effectively during interviews.
✨Tip Number 4
Brush up on your Python skills, especially in relation to debugging and working with codebases. Being able to demonstrate your technical proficiency in Python during the interview will be crucial, as it’s a key requirement for this role.
We think you need these skills to ace Research Assistant – AI Agents & LLM Prototyping
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in prototyping and testing AI agents or large language models. Include specific projects or roles that demonstrate your skills in Python and any relevant frameworks like MCP or LangChain.
Craft a Strong Cover Letter: Write a cover letter that directly addresses the key responsibilities mentioned in the job description. Explain how your background aligns with their needs, particularly your experience with prompt engineering and debugging AI tools.
Showcase Technical Skills: In your application, emphasise your proficiency in Python and any experience you have with SQL or data analysis. Mention any familiarity with source control systems like Git, as this is relevant to the role.
Highlight Relevant Experience: Detail your past experiences related to machine learning, deep learning, or natural language processing. Use specific examples to illustrate how you've contributed to similar projects, especially those involving generative AI or LLM research.
How to prepare for a job interview at US Tech Solutions
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and any experience you have with AI agent frameworks like MCP and LangChain. Be prepared to discuss specific projects where you've implemented these skills, as this will demonstrate your hands-on experience.
✨Prepare for Prompt Engineering Questions
Since the role involves designing test prompts, be ready to explain your approach to prompt engineering. Think of examples where you've created effective prompts and how they influenced the performance of AI agents.
✨Demonstrate Problem-Solving Abilities
The job requires troubleshooting AI agent tool calls, so be prepared to discuss how you've approached debugging in the past. Share specific instances where you identified issues and how you resolved them, showcasing your analytical skills.
✨Familiarise Yourself with Evaluation Metrics
Understanding how to create internal benchmarks for evaluating AI agent performance is crucial. Brush up on common evaluation metrics used in AI research and be ready to discuss how you would apply them in this role.