ML Engineer II

We're in search of a seasoned ML Engineer to spearhead innovative projects as an individual contributor. You'll get to dive deep into cutting-edge technology where you'll tinker with LLMs, fine-tune models for the customer success domain, build search/retrieval technology, and implement new workflow automation systems. Responsibilities: You will be responsible for developing production-ready inference pipelines, managing model deployment and versioning, and ensuring effective validation processes.You'll also be working hand in hand with cross-functional teams in product and engineering to shape our machine learning products, bringing a synthesis of innovation and pragmatism, while ensuring alignment with customer interests and best practices. Requirements: Deep expertise working as a machine learning engineer or similar role, focusing on NLP.Demonstrated experience building, evaluating, and testing machine learning models.Led the deployment and management of ML models in a production setting.Strong programming skills with proven experience implementing Python-based solutions using good software engineering design practices.Familiar with common DS libraries (NumPy, pandas, and scikit-learn).Experience designing and evaluating ML A/B tests.Previous experience at a high-growth, fast-paced VC-backed startup, or tech lead position at a larger organisation.Bonus experience LLMs and related tooling: GPT, Langchain, HuggingFace, etc.Deep learning techniques, reinforcement learning, and generative models.Common ML frameworks (like PyTorch, TensorFlow, and Keras) worked with text embeddings and transformer models. We're in search of a seasoned ML Engineer to spearhead innovative projects as an individual contributor. You'll get to dive deep into cutting-edge technology where you'll tinker with LLMs, fine-tune models for the customer success domain, build search/retrieval technology, and implement new workflow automation systems. Responsibilities: You will be responsible for developing production-ready inference pipelines, managing model deployment and versioning, and ensuring effective validation processes.You'll also be working hand in hand with cross-functional teams in product and engineering to shape our machine learning products, bringing a synthesis of innovation and pragmatism, while ensuring alignment with customer interests and best practices. Requirements: Deep expertise working as a machine learning engineer or similar role, focusing on NLP.Demonstrated experience building, evaluating, and testing machine learning models.Led the deployment and management of ML models in a production setting.Strong programming skills with proven experience implementing Python-based solutions using good software engineering design practices.Familiar with common DS libraries (NumPy, pandas, and scikit-learn).Experience designing and evaluating ML A/B tests.Previous experience at a high-growth, fast-paced VC-backed startup, or tech lead position at a larger organisation.Bonus experience LLMs and related tooling: GPT, Langchain, HuggingFace, etc.Deep learning techniques, reinforcement learning, and generative models.Common ML frameworks (like PyTorch, TensorFlow, and Keras) worked with text embeddings and transformer models.