The Global Talent Co. - AI Engineer
Requirements
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field5+ years of experience as an AI/ML Engineer or similar role. • AI/ML Engineer or similar role. • Hands-on experience with LLMs (OpenAI GPT-4, Anthropic Claude, Google Gemini, Llama). • LLMs (OpenAI GPT-4, Anthropic Claude, Google Gemini, Llama). • Strong expertise in building RAG systems, agent frameworks, and LLM chains. • RAG systems, agent frameworks, and LLM chains. • Proficiency in Python and experience with machine learning frameworks such as PyTorch. • Python • PyTorch. • Solid understanding of machine learning algorithms, deep learning, and NLP. • machine learning algorithms, deep learning, and NLP. • Experience evaluating ML models and LLMs using metrics and validation methodologies. • ML models and LLMs using metrics and validation methodologies. • Experience with SQL (Postgres) and data warehouse management (Snowflake preferred)Strong problem-solving and analytical skills. • SQL (Postgres) • Snowflake preferred • Excellent communication skills and ability to work in a multidisciplinary environment. • multidisciplinary environment. • Experience deploying AI models on cloud platforms (AWS, Google Cloud, Azure). • cloud platforms (AWS, Google Cloud, Azure). • Open-source contributions in AI projects or participation in AI research communities. • AI research communities. • Experience with big data technologies (Hadoop, Spark). • big data technologies (Hadoop, Spark). • Domain knowledge in industries such as finance, healthcare, retail, or technology • finance, healthcare, retail, or technology • AI-powered platforms • machine learning and large language models • If you're passionate about advancing AI and eager to make an impact, this is an opportunity to contribute to shaping the future of AI innovation. 🚀 • advancing AI • AI innovation
Responsibilities
• Design and implement machine learning models and AI algorithms for applications such as OCR, retrieval-augmented generation (RAG), conversational agents, and content generation. • machine learning models and AI algorithms • Develop and optimize prompts for LLMs to improve model outputs and align with business objectives. • prompts for LLMs • Evaluate and fine-tune ML models and LLMs using rigorous testing and validation methodologies. • ML models and LLMs • Collect, preprocess, and manage large datasets to support AI model training and deployment. • large datasets • Collaborate with software engineers, data scientists, and product teams to integrate AI models into products and services. • software engineers, data scientists, and product teams • Stay updated on the latest advancements in generative AI, LLMs, and machine learning frameworks. • generative AI, LLMs, and machine learning frameworks. • Deploy AI models into production environments and monitor performance, making necessary adjustments over time. • production environments
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