Lead AI Software Engineer
Klaviyo
•
Boston, MA
0
0
0
0
Not Applicable
Posted April 5, 2026
Job link
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Responsibilities
Commitments
Responsibilities
- Lead the design and development of backend and ML systems that scale to serve 182K+ customers.
- Build robust, reliable, and efficient data processing and model-serving pipelines that power production ML models.
- Develop and optimize predictive systems (e.g., conversion likelihood, engagement ranking, personalization, anomaly detection).
- Architect systems and services that enable our AI agents to learn and improve autonomously from reward or outcome signals.
- Collaborate cross-functionally to translate business challenges into scalable, measurable ML solutions.
- Collaborate with software engineers and product managers to turn predictive models into intuitive product features for our customers.
- Mentor engineers and help evolve Klaviyo’s ML engineering best practices, tooling, and architecture.
- Foster a culture of ownership, experimentation, and data-driven innovation across teams.
Commitments
We use Covey as part of our hiring and / or promotional process.
For jobs or candidates in NYC, certain features may qualify it as an AEDT.
As part of the evaluation process we provide Covey with job requirements and candidate submitted applications.
We began using Covey Scout for Inbound on April 3, 2025.
Please see the independent bias audit report covering our use of Covey here
Massachusetts Applicants
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.
An employer who violates this law shall be subject to criminal penalties and civil liability.
We provide accommodations as needed.
Not Met Priorities
What still needs stronger evidence
Requirements
- 7–10 years of experience in machine learning engineering or applied software engineering, with a focus on classical ML and predictive modeling.
- Deep understanding of supervised learning methods such as random forests, XGBoost, logistic regression, and ensemble techniques.
- Proven track record of building and scaling production-grade ML systems end to end (data pipelines, training, deployment, and monitoring).
- Experienced backend engineer comfortable with distributed systems and high-scale architectures.
- Proficient in Python and modern frameworks (FastAPI, Django preferred).
- Skilled with big data and streaming technologies (Apache Spark, Kafka, Hadoop).
- Hands-on with asynchronous processing and distributed task queues (Celery, SQS, RabbitMQ, Redis).
- Strong understanding of databases and ORMs (SQLAlchemy, Alembic) and cloud-native architectures (AWS, Kubernetes, CI/CD).
- Excellent communicator who can set technical direction, influence product strategy, and mentor junior engineers.
- Curious, pragmatic, and passionate about building AI systems that drive measurable business impact.
Preferred Skills
- Experience training and deploying ML models in production environments that generated measurable impact.
- Familiarity with reinforcement learning or agentic AI systems that adapt based on outcome or reward signals.
Education
- (Not required) – 7–10 years of experience in machine learning engineering or applied software engineering, with a focus on classical ML and predictive modeling.
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
Lead AI Engineer
At Klaviyo, we believe the future of software lies not in productivity tools for human users but in systems that can learn, run, and optimize themselves based on measurable outcomes. We’ve built the infrastructure and applications that power the interface between businesses and consumers — supporting over 182,000 customers , billions of consumer profiles , and hundreds of billions of customer interactions .
Now, we’re building the next generation of AI and machine learning technologies to power these products — enabling AI agents that can automatically create, execute, and optimize marketing and customer experience strategies for any business.
As a Lead AI Engineer , you’ll take ownership of designing, building, and scaling the backend and machine learning systems that form the foundation of Klaviyo’s AI strategy. You’ll partner closely with product managers, data scientists, and engineers to deliver intelligent, outcome-driven systems that operate at massive scale — while mentoring others and setting technical direction for the team.
How You Will Make a Difference
Lead the design and development of backend and ML systems that scale to serve 182K+ customers.
Build robust, reliable, and efficient data processing and model-serving pipelines that power production ML models.
Develop and optimize predictive systems (e.g., conversion likelihood, engagement ranking, personalization, anomaly detection).
Architect systems and services that enable our AI agents to learn and improve autonomously from reward or outcome signals.
Collaborate cross-functionally to translate business challenges into scalable, measurable ML solutions.
Collaborate with software engineers and product managers to turn predictive models into intuitive product features for our customers.
Mentor engineers and help evolve Klaviyo’s ML engineering best practices, tooling, and architecture.
Foster a culture of ownership, experimentation, and data-driven innovation across teams.
Who You Are
7–10 years of experience in machine learning engineering or applied software engineering, with a focus on classical ML and predictive modeling.
Deep understanding of supervised learning methods such as random forests, XGBoost, logistic regression, and ensemble techniques.
Proven track record of building and scaling production-grade ML systems end to end (data pipelines, training, deployment, and monitoring).
Experienced backend engineer comfortable with distributed systems and high-scale architectures.
Proficient in Python and modern frameworks (FastAPI, Django preferred).
Skilled with big data and streaming technologies (Apache Spark, Kafka, Hadoop).
Hands-on with asynchronous processing and distributed task queues (Celery, SQS, RabbitMQ, Redis).
Strong understanding of databases and ORMs (SQLAlchemy, Alembic) and cloud-native architectures (AWS, Kubernetes, CI/CD).
Excellent communicator who can set technical direction, influence product strategy, and mentor junior engineers.
Curious, pragmatic, and passionate about building AI systems that drive measurable business impact.
Nice to Have
Experience training and deploying ML models in production environments that generated measurable impact.
Familiarity with reinforcement learning or agentic AI systems that adapt based on outcome or reward signals.
#indeedRD
We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025.
Please see the independent bias audit report covering our use of Covey here
Massachusetts Applicants
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
Base Pay Range For US Locations:
$176,000—$264,000 USD
Get to Know Klaviyo
We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls.
By clicking "Submit Application" you consent to Klaviyo processing your Personal Data in accordance with our Job Applicant Privacy Notice. If you do not wish for Klaviyo to process your Personal Data, please do not submit an application. You can find our Job Applicant Privacy Notice here and here (FR).
Lead AI Engineer
At Klaviyo, we believe the future of software lies not in productivity tools for human users but in systems that can learn, run, and optimize themselves based on measurable outcomes. We’ve built the infrastructure and applications that power the interface between businesses and consumers — supporting over 182,000 customers , billions of consumer profiles , and hundreds of billions of customer interactions .
Now, we’re building the next generation of AI and machine learning technologies to power these products — enabling AI agents that can automatically create, execute, and optimize marketing and customer experience strategies for any business.
As a Lead AI Engineer , you’ll take ownership of designing, building, and scaling the backend and machine learning systems that form the foundation of Klaviyo’s AI strategy. You’ll partner closely with product managers, data scientists, and engineers to deliver intelligent, outcome-driven systems that operate at massive scale — while mentoring others and setting technical direction for the team.
How You Will Make a Difference
Lead the design and development of backend and ML systems that scale to serve 182K+ customers.
Build robust, reliable, and efficient data processing and model-serving pipelines that power production ML models.
Develop and optimize predictive systems (e.g., conversion likelihood, engagement ranking, personalization, anomaly detection).
Architect systems and services that enable our AI agents to learn and improve autonomously from reward or outcome signals.
Collaborate cross-functionally to translate business challenges into scalable, measurable ML solutions.
Collaborate with software engineers and product managers to turn predictive models into intuitive product features for our customers.
Mentor engineers and help evolve Klaviyo’s ML engineering best practices, tooling, and architecture.
Foster a culture of ownership, experimentation, and data-driven innovation across teams.
Who You Are
7–10 years of experience in machine learning engineering or applied software engineering, with a focus on classical ML and predictive modeling.
Deep understanding of supervised learning methods such as random forests, XGBoost, logistic regression, and ensemble techniques.
Proven track record of building and scaling production-grade ML systems end to end (data pipelines, training, deployment, and monitoring).
Experienced backend engineer comfortable with distributed systems and high-scale architectures.
Proficient in Python and modern frameworks (FastAPI, Django preferred).
Skilled with big data and streaming technologies (Apache Spark, Kafka, Hadoop).
Hands-on with asynchronous processing and distributed task queues (Celery, SQS, RabbitMQ, Redis).
Strong understanding of databases and ORMs (SQLAlchemy, Alembic) and cloud-native architectures (AWS, Kubernetes, CI/CD).
Excellent communicator who can set technical direction, influence product strategy, and mentor junior engineers.
Curious, pragmatic, and passionate about building AI systems that drive measurable business impact.
Nice to Have
Experience training and deploying ML models in production environments that generated measurable impact.
Familiarity with reinforcement learning or agentic AI systems that adapt based on outcome or reward signals.
#indeedRD
We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025.
Please see the independent bias audit report covering our use of Covey here
Massachusetts Applicants
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
Base Pay Range For US Locations:
$176,000—$264,000 USD
Get to Know Klaviyo
We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls.
By clicking "Submit Application" you consent to Klaviyo processing your Personal Data in accordance with our Job Applicant Privacy Notice. If you do not wish for Klaviyo to process your Personal Data, please do not submit an application. You can find our Job Applicant Privacy Notice here and here (FR).