Senior AI/ML Engineer

February 15

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Drips

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Drips helps companies engage with their consumers more effectively. How do we do it? Through an AI-powered, conversational outreach platform that includes human-like two-way texting, scheduled calling and voicemail messages.

Lead Follow-Up • Lead Qualification • Transfers • SMS for Business • Conversational Outreach

51 - 200 employees

💰 Venture Round on 2021-10

📋 Description

•As a Senior AI/ML Engineer, you will be responsible for designing, developing, maintaining, deploying and monitoring NLP , AI, and machine learning models that drive the core of the Drips Platform and products. •You will be part of our growing AI team comprised of AI Engineer, data scientists, and data analysts. •You will be collaborating with Engineers, QA, Operations, Product management and other key stakeholders in the company. •Design, develop, deploy and monitor NLP AI and Machine Learning models. •Troubleshoot and maintain existing AI models. •Integrate AI/ML models into production pipelines and configure for high levels of scalability and reliability. •Collaborate with the Development and QA teams. •Work with data scientists and utilize tools, techniques, and industry best practices to manage large volumes of data. •Handle MLOps and automate data retrieval, training, testing and deployment of models. •Stay on top of the latest AI research and innovations.

🎯 Requirements

•Five or more years of hands-on experience in AI/ML senior engineering roles focused on Natural Language Processing use cases. •Expert in Python with experience in libraries/frameworks such as PyTorch, TensorFlow, scikit-learn, Keras, Pandas, and NumPy. •Experienced in using SQL and working with databases. •A degree in Computer Science with specialization in AI or Machine Learning, or equivalent combination of education and work experience. •Solid, hands-on understanding of AI and machine learning algorithms, leveraging Deep learning using RNNs, BERT for contextual understanding and Fine-tuning LLMs. •Experience with deploying AI/ML models in public cloud environments like Azure and AWS, exposure to LLMs, and comfort with DevOps functions related to MLOps pipelines. •Experience with intent classification on large datasets, applying unsupervised learning techniques, and executing end-to-end modeling. •Ph.D. in any of the areas related to AI/ML or a closely related discipline•Practical experience working in companies dealing with conversational text and voice. •Experience with Hugging Face models, Onnx runtimes, LangChain, and other modern AI frameworks. •Contributions to open-source projects, authorship of blogs on AI/ML and other technical areas, or publication of research papers in relevant fields.