Machine Learning Engineer

Summary

Join Twilio's Efficiency Engineering team as a Machine Learning Engineer. This role involves developing and deploying AI/ML models, collaborating with cross-functional teams, and leveraging advanced technologies. You will build supervised machine learning models and GenAI/LLM-powered applications to meet the needs of Twilio's diverse customer base. The position requires 5+ years of experience in data engineering, applied ML, and software engineering. Twilio offers competitive pay, generous time off, parental and wellness leave, healthcare, and a retirement savings program. The role is remote with some travel.

Requirements

• 5+ years of data engineering, applied ML & software engineering experience
• Develop and Deploy AI pipelines & models: Build and deploy data pipelines & 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, OpenSearch), MySQL, Airtable, Pinecone 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, OpenSearch), 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

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