Turing - Staff Gen AI Engineer
Requirements
• 8+ years of professional experience in building Machine Learning models & systems • 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents. • Experience in driving the engineering team toward a technical roadmap. • Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must. • Understanding of Cloud services, including Azure, GCP, or AWS • Excellent communication skills to effectively collaborate with business SMEs • Values: • Values: • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. • We are client first • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection • We work at Start-Up Speed: • We are Al forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. • We are Al forward: • Advantages of joining Turing: • Amazing work culture (Super collaborative & supportive work environment; 5 days a week) • Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience) • Competitive compensation • Flexible working hours
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. • Develop and optimize LLM-based solutions • 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. • Codebase ownership • Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. • Cloud integration • 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. • Cross-functional collaboration • Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development. • Mentoring and guidance • 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. • Continuous innovation
Benefits
• Flexible working hours
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