ABOUT THIS FEATURED OPPORTUNITY

The Python Developer and Prompt Engineer will work directly with client teams as well as research and development teams to use data science models and strategies to improve data quality and synthesize data. This involves leveraging multimodal models and large language models (LLMs) to synthesize and annotate image and text data, using tools like ChatGPT and Gemini to scale annotations across large datasets ranging from 100K to 500K entries. As models improve, they become increasingly effective for pre-annotation, streamlining human annotation efforts when needed. The role requires complex data analysis using machine learning models for data mining and processing large-scale datasets (GB/TB). The ideal candidate will hold a degree in computer science, data science, artificial intelligence, linguistics, or a related field, and have hands-on experience with NLP models, content generation tools, or AI systems. Backgrounds in technical writing or human-computer interaction (HCI) are highly valuable. This position requires close collaboration with AI developers, data scientists, and product teams to ensure AI output aligns with business objectives, and strong communication skills are essential to document and clearly explain prompt engineering processes and outcomes.

THE OPPORTUNITY FOR YOU

Join a dynamic and innovative team where you will have the opportunity to work at the forefront of AI-driven data synthesis and annotation. You’ll apply your technical expertise to optimize large language models and multimodal AI systems, significantly improving the efficiency and quality of large-scale datasets. This is a chance to build critical AI capabilities, work on high-impact projects with cross-functional teams, and contribute directly to the future of AI-powered data solutions.

KEY SUCCESS FACTORS

• Programming Knowledge: Proficiency in languages like Python to interact with AI models via APIs.
• Experience with AI Tools/Platforms: Familiarity with AI frameworks such as GPT, OpenAI, Gemini, Hugging Face, or similar tools used to develop or refine AI models.
• Data Handling: Expertise in working with large datasets and testing different scenarios and datasets to optimize prompts and model performance.

NICE TO HAVES

• Experience with prompt engineering techniques and best practices.
• Strong communication and collaboration skills to work effectively with cross-functional teams, including AI developers, data scientists, and product teams.
• Excellent analytical skills with the ability to think creatively and work independently on complex data analysis and model optimization tasks.

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