Staff Machine Learning Engineer, Twilio

$184.5-271.3k

Salary is applicable to CA, CO, NY, WA and Washington D.C. candidates only, is partially dependent on location and may vary on further locations

SQL

AWS

Python

Airtable

Salesforce

MySQL

NumPy

Pandas

Scikit-Learn

Keras

Sagemaker

Zendesk

Sage

Senior and Expert level

Remote in US

More information about location

Cloud communications software

Be an early applicant

Cloud communications software

1001+ employees

B2BArtificial IntelligenceCommunicationInternet of ThingsMachine LearningCloud Computing

Be an early applicant

$184.5-271.3k

Salary is applicable to CA, CO, NY, WA and Washington D.C. candidates only, is partially dependent on location and may vary on further locations

SQL

AWS

Python

Airtable

Salesforce

MySQL

NumPy

Pandas

Scikit-Learn

Keras

Sagemaker

Zendesk

Sage

Senior and Expert level

Remote in US

More information about location

1001+ employees

B2BArtificial IntelligenceCommunicationInternet of ThingsMachine LearningCloud Computing

Company mission

To enable innovators across every industry - from emerging leaders to the world’s largest organisations - to reinvent how companies engage with their customers.

Job

Company

Role

Who you are

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

Desirable

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

What the job involves

Twilio is experiencing rapid growth and is seeking a Staff Machine Learning Engineer with a strong Data Science, Machine Learning & Predictive Modeling background to expand and enhance our Efficiency Engineering team's AI function
This team is responsible for developing cutting edge solutions leveraging AI & Data Science for external and internal customers
As a Staff Machine Learning Engineer within Efficiency Engineering, you will be instrumental in developing supervised machine learning (ML) propensity models as well as state-of-the-art GenAI/LLM-powered applications
Your solutions will cater to the dynamic needs of Twilio’s diverse verticals and our extensive customer base
This role offers an exciting opportunity to harness the power of advanced machine learning technologies to drive innovation and efficiency
As a member of this team, you will have the opportunity to work on groundbreaking projects that directly impact the efficiency and success of our customers
You will collaborate with talented professionals who are as driven and enthusiastic about AI and Machine Learning as you are
Your contributions will be crucial in shaping the future of AI at Twilio, and you will have the support and resources needed to innovate and excel
Develop and Deploy AI/ML Models: Build and deploy machine learning models by leveraging NLP, recommendation systems & Gen AI-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 (Sage maker, Lambda, S3, Kendra), MySQL, Air table, 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 Zen desk 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 Gen AI use cases and solutions

Our take

Traditionally, it has been difficult for businesses to establish communications systems in-house. Twilio was founded from frustration with this expensive and cumbersome process, providing easy-to-use APIs to let businesses send and receive telephone and text communications.

From these beginnings, the company has expanded through acquisitions and product development to provide a suite of services around market data and customer engagement. It is now a market leader in this space, and has developed a customer base of more than 150,000 businesses including enterprise brands such as Deliveroo, Duolingo and Toyota.

With that said, aggressive expansion and lack of maturity in some of its products has impacted the company's efficiency, and like many of its peers it has been forced to restructure heavily to remain competitive. Coming out of this restructuring, the company will focus on profitability, streamlining decision making and R&D to put itself in good stead for future success.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

35% employee growth in 12 months

Glassdoor (3.7)

Company

Funding (last 2 of 6 rounds)

Jul 2015

$130m

SERIES E

Jun 2013

$70m

SERIES D

Total funding: $250.7m

Company benefits

Generous annual time off in all countries
Comprehensive health programs
Programs to help our employees plan for their retirement needs
Generous maternity, paternity, and adoption leaves, as well as family medical care leave
Build and present a Twilio app to earn your Twilio track jacket and receive $30 per month for e-books for continued learning and education
Variety of snacks, drinks, and catered meals in each of our locations
Work from home opportunities

Company HQ

Financial District, San Francisco, CA

Leadership

Khozema Shipchandler

(CEO, not founder)

Has been at the company since 2018, beginning as CFO then working as COO, President of Communications then CEO. Prior to this, spent 20 years at GE, ultimately as CCO of GE Digital.

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