Machine Learning Engineer

Summary

Join Twilio's Efficiency Engineering team as a Staff, Machine Learning Engineer. You will develop and deploy AI/ML models, leveraging NLP, recommendation systems, and GenAI-powered applications. Collaboration with various teams is crucial to implement and refine models driving business outcomes. The role requires utilizing a specific technical stack, including Python, SQL, R, and AWS services. You will integrate enterprise data sources and harness the power of LLMs. This position offers an opportunity to work on groundbreaking projects and contribute to the future of AI at Twilio.

Requirements

• 6+ years of applied ML 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

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, 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

Preferred Qualifications

• 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

Benefits

• Competitive pay
• Generous time-off
• Ample parental and wellness leave
• Healthcare
• A retirement savings program
• Health care insurance
• 401(k) retirement account
• Paid sick time
• Paid personal time off
• Paid parental leave