Staff Machine Learning Engineer (L4)

Twilio is a remote-first company revolutionizing communications with innovative solutions. They are seeking a Staff Machine Learning Engineer to develop AI-powered tools and applications that enhance customer support operations through advanced machine learning technologies.

Responsibilities:

• Develop and Deploy AI/ML Models: Build and deploy machine learning models by leveraging NLP, recommendation systems & GenAI-powered applications, to production environments, ensuring they meet the diverse needs of Twilio's verticals and customer base
• Collaborate Across Teams: Work closely with product, program, analytics, and engineering teams to implement and refine machine learning, statistical, and forecasting models that drive business outcomes
• Utilize Advanced Technical Stack: Leverage our technical stack, including Python, SQL, R, AWS (Sagemaker, Lambda, S3, Kendra), MySQL, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Keras, to develop robust and scalable AI/ML solutions
• Integrate Enterprise Data Sources: Effectively utilize enterprise data sources like Salesforce and Zendesk to inform model development and enhance predictive accuracy
• Harness the Power of LLMs: Apply knowledge of Large Language Models (LLMs) such as OpenAI's GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative GenAI use cases and solutions

Requirements:

• 5+ years of applied ML engineering experience
• Develop and Deploy AI Models: Build and deploy machine learning models leveraging NLP techniques and GenAI-powered applications, to production environments, ensuring they meet the diverse needs of Twilio's verticals and customer base
• Collaborate Across Teams: Work closely with product, program, analytics, and engineering teams to implement and refine machine learning, statistical, and forecasting models that drive business outcomes
• Utilize Advanced Technical Stack: Leverage our technical stack, including Python, SQL, R, AWS (Sagemaker, Lambda, S3, Kendra), MySQL, Airtable, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Keras, to develop robust and scalable AI/ML solutions
• Integrate Enterprise Data Sources: Effectively utilize enterprise data sources like Salesforce and Zendesk to inform model development and enhance predictive accuracy
• Harness the Power of LLMs: Apply knowledge of Large Language Models (LLMs) such as OpenAI's GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative GenAI use cases and solutions
• Familiarity with using LLMs (OpenAI, Claude, Gemini, Llama etc.), RAG, Agents, Model Fine-tuning, Few-shot prompting, Prompt Engineering
• Experience with Python-specific frameworks such as Llamaindex, Langchain, Streamlit, Gradio, FastHTML, Chainlit etc
• Research background & experience writing papers for top-tier peer-reviewed conferences or journals