
Staff Machine Learning Engineer, L4
Twilio
full-time
Posted on:
Location Type: Remote
Location: California • Connecticut • United States
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Salary
💰 $188,240 - $276,700 per year
Job Level
About the role
- 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
Benefits
- Health care insurance
- 401(k) retirement account
- Paid sick time
- Paid personal time off
- Paid parental leave
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningnatural language processingrecommendation systemsstatistical modelsforecasting modelsPythonSQLRlarge language modelsGenAI
Soft Skills
collaborationteamworkcommunicationproblem-solvingadaptability