Andiamo
We are seeking a talented Generative AI Engineer to help design and build the next generation of AI-powered applications at a high-growth, pre-IPO technology company.
You will work on applying large language models (LLMs), multimodal AI, and cutting-edge generative techniques to create products that transform how our customers interact with data, content, and decision-making systems.
This is a hands-on engineering role at the intersection of AI research and scalable product development. You will collaborate with data scientists, ML engineers, and product managers to prototype, deploy, and optimize generative AI systems that deliver measurable customer and business impact.
Responsibilities
Develop Generative Applications: Build production-ready systems leveraging LLMs and generative models for NLP, code, and multimodal use cases. Integrate with Products: Design APIs and services that embed generative AI capabilities into customer-facing applications. Optimize Models: Fine-tune, distill, and adapt foundation models to specific tasks and domains for efficiency and performance. Leverage Retrieval & Memory: Implement retrieval-augmented generation (RAG), vector search, and embeddings for context-aware AI solutions. Ensure Reliability: Build monitoring and evaluation pipelines to track model quality, detect drift, and maintain trustworthiness in production. Collaborate Cross-Functionally: Work with researchers and product leaders to translate cutting-edge AI into practical features. Stay Ahead: Keep current with state-of-the-art generative AI research and frameworks, bringing new ideas and approaches into the company. Requirements
Professional Experience: 3-7 years in applied ML/AI engineering, with at least 1-2 years working on generative AI, LLMs, or related areas. Technical Skills: Proficiency in Python, strong experience with ML/AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex). LLM Experience: Hands-on experience fine-tuning or deploying large language models, and familiarity with APIs such as OpenAI, Anthropic, or similar. Infrastructure Knowledge: Experience with cloud ML platforms (AWS Sagemaker, GCP Vertex AI, Azure ML) and vector databases (Pinecone, Weaviate, Milvus, FAISS). Systems Thinking: Ability to design scalable pipelines for training, inference, and integration into production systems. Collaboration: Strong communication skills and ability to partner across engineering, product, and research teams. Education: Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or a related field; PhD a plus. This is a unique opportunity to shape the future of generative AI at a pre-IPO company with $500M+ in funding. As a Generative AI Engineer, you’ll work with state-of-the-art models, solve complex problems at scale, and bring transformative AI capabilities directly to customers.
#J-18808-Ljbffr
Develop Generative Applications: Build production-ready systems leveraging LLMs and generative models for NLP, code, and multimodal use cases. Integrate with Products: Design APIs and services that embed generative AI capabilities into customer-facing applications. Optimize Models: Fine-tune, distill, and adapt foundation models to specific tasks and domains for efficiency and performance. Leverage Retrieval & Memory: Implement retrieval-augmented generation (RAG), vector search, and embeddings for context-aware AI solutions. Ensure Reliability: Build monitoring and evaluation pipelines to track model quality, detect drift, and maintain trustworthiness in production. Collaborate Cross-Functionally: Work with researchers and product leaders to translate cutting-edge AI into practical features. Stay Ahead: Keep current with state-of-the-art generative AI research and frameworks, bringing new ideas and approaches into the company. Requirements
Professional Experience: 3-7 years in applied ML/AI engineering, with at least 1-2 years working on generative AI, LLMs, or related areas. Technical Skills: Proficiency in Python, strong experience with ML/AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex). LLM Experience: Hands-on experience fine-tuning or deploying large language models, and familiarity with APIs such as OpenAI, Anthropic, or similar. Infrastructure Knowledge: Experience with cloud ML platforms (AWS Sagemaker, GCP Vertex AI, Azure ML) and vector databases (Pinecone, Weaviate, Milvus, FAISS). Systems Thinking: Ability to design scalable pipelines for training, inference, and integration into production systems. Collaboration: Strong communication skills and ability to partner across engineering, product, and research teams. Education: Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or a related field; PhD a plus. This is a unique opportunity to shape the future of generative AI at a pre-IPO company with $500M+ in funding. As a Generative AI Engineer, you’ll work with state-of-the-art models, solve complex problems at scale, and bring transformative AI capabilities directly to customers.
#J-18808-Ljbffr