LLM S2 Annotator (CUA Trajectory Specialist)
Turing • Remote, USA • Posted 29 days ago
Education
Any
Type
Pay Rate
$50/task
Posted
29d ago
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About this Role
Title - Sr./Staff/Principal GenAI Engineer
Location - NYC, NY (Onsite)
Fulltime
About Turing
Based in Palo Alto, California, Turing is the world’s first AI-powered tech services company. It has reimagined tech services from the ground up with AI by offering AI-vetted and matched talent, AI-accelerated development, and access to AI transformation experts who have built many of the most iconic Silicon Valley companies.
Founded in 2018, the company has experienced tremendous growth with over two million global developers on its Talent Cloud and 900+ clients. Turing has received numerous awards, including Forbes’s 2022 “One of America’s Best Startup Employers,” being ranked #1 in The Information’s 2021 Annual List of most promising B2B Companies and Fast Company’s “Annual List of the World’s Most Innovative Companies.”
The company’s leadership team comprises both AI technologists from leading organizations including Meta, Google, Microsoft, Apple, Amazon, Twitter, Stanford, Caltech, MIT as well as tech consulting veterans from Accenture, Cognizant, Capgemini, McKinsey, Bain, and more.
About the role:
Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises.
Mandatory Skills -
Agentic AI/Langgraph MCP Graph DB
Required skills
8+ years for Sr GenAI Engineer and 10+ years for Staff/Principal GenAI Engineer, of professional experience in building Machine Learning models & systems 3+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents. Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must. Understanding of Cloud services from various cloud services from Azure, GCP, or AWS for building the GenAI applications Excellent communication skills to effectively collaborate with business SMEs
Roles & Responsibilities
Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures. Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices. Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products. Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development. Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.
Vetting Process
Technical Discussion Zoom (Live Coding while sharing screen) - 1 hour Delivery Connect - ½ Hour (Zoom) In person interview at NYC, NY
Requirements
- Must be eligible to work in one of: Remote, USA
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
- Bachelor's degree or equivalent professional experience
- Demonstrated expertise in Software Engineering
Compensation Analysis
Work from anywhere, at any time. This fully remote position ($50/hr) breaks down geographic barriers, allowing you to earn US-competitive rates regardless of your local market. It is a perfect stepping stone for building a career in the data labeling and AI training ecosystem.
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Frequently Asked Questions
Do I need to be a software engineer?
Not anymore. Turing built its reputation matching senior engineers with Silicon Valley companies, but they have heavily pivoted into AGI infrastructure. They now hire non-engineering domain experts, technical writers, and researchers for post-training data annotation and RLHF. A strong analytical background and excellent English are required, but you do not need to code.
How does matching work?
Turing calls it the 'Intelligent Talent Cloud.' You build a profile and go through deep vetting — automated tests, an AI-powered interview, and practical skill assessments. Once vetted, Turing's algorithm automatically surfaces you to partner companies (Fortune 500s and top AI labs). You don't browse job boards or bid on work — matches come to you.
How does payment work?
You are hired as an independent contractor, responsible for your own local taxes. Turing collects payment from the client and pays you monthly in USD via Deel, Payoneer, or direct bank/wire transfer. Monthly pay is standard for long-term contract roles — if you need weekly cash flow, this structure requires adjustment.
What does the work actually look like?
It is practical, hands-on data work. You might be recording short videos, categorizing images, rating text responses, or analyzing data. The tasks are designed to be short and distinct—typically 5-60 minutes per task.
How flexible is the schedule?
Extremely. This is true "log in and work" flexibility. You can usually work for 20 minutes or 4 hours depending on your availability. There are rarely minimum hour requirements, making it ideal for side income.
Is there an interview?
Usually, no. Hiring for these roles is almost entirely based on passing an automated assessment or "qualification" task. If you pass the test, you get access to the work.