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Skills: Machine Learning, Deep Learning, Recommender Systems, Language Modeling, Generative AI
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SeniorVisa sponsorship
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Palo Alto, California, United States · Remote Solely
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You will train and deploy large-scale machine learning models and AI agents to optimize marketing strategies and customer experiences. Additionally, you will collaborate with engineering and product teams to integrate conversational AI and generative models into the company's software.
Requirements
Candidates must hold an advanced degree in Computer Science or a related field and possess at least 5 years of experience in AI or machine learning. You are expected to have a proven track record of leading large-scale projects and deploying models into production environments.
Full job description
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.
Sr. Machine Learning Engineer
Palo Alto, CA (Onsite 5x a week)
At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 200,000+ customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We have a big opportunity to build state-of-the-art AI and machine learning technologies at Klaviyo to power our products and develop AI agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business.
As a Sr. Machine Learning Engineer at Klaviyo, you will help build models that extract insights from the massive streams of data that Klaviyo ingests continuously. You will apply cutting-edge techniques from deep learning, recommender systems, language modeling, and more to integrate artificial intelligence into our product and bring customers value. You will need to deep dive into the product and the code to understand and contribute to solutions with your technical knowledge and experiences. You will be working with partners in Engineering, Product, and Design to solve challenging problems, and talking to stakeholders and customers firsthand.
Things you’ll do & make a difference
Train and deploy large-scale Machine Learning models in production systems to improve the values our product provide to our customers
Create AI engines or agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business and demonstrably outperform our human customers at Klaviyo.
Introduce conversational AI interfaces into our software to make our customers more efficient users of our products.
Build generative AI models that can automatically generate content for marketing given customer input on context, to maximize customer ROI or improve customers’ productivity.
Work in high impact environments with fast experimentation and product development cycles
What we are looking for:
Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
5+ years of experience in AI, machine learning, or related fields, with a track record of successfully leading large-scale AI / machine learning projects launched in products with a significant impact on users / customers.
Experience with machine learning frameworks such as Huggingface, PyTorch, Tensorflow, Keras; Experience with distributed training with Spark, Ray, etc.
Experience leading technical projects and working with engineering teams and product managers successfully to deliver customer-facing features
Experience of developing and putting machine learning models into production, while also owning and maintaining production models long term
Experience owning the full product lifecycle of ML development, including defining success metrics, designing and analyzing A/B tests, and iterating based on result
Experience mentoring others
Nice to have:
Experience with recommendation systems, including designing, training, and deploying recommendation models, as well as building retrieval and ranking systems.
Experience working in B2B businesses and interacting with customers directly
Experience developing technical roadmaps for solving complex business problems using Machine Learning
Experience fine-tuning and productionizing transformer-based models at scale, particularly large language models.
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:
$196,000—$294,000 USD
This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
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.
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).
Klaviyo is the autonomous CRM for B2C brands, built to turn what you know about your customers into real growth.
Industry
Marketing Services
Company size
1,001-5,000 employees
Founded
2012
Headquarters
Boston, Massachusetts
LinkedIn followers
178,358
Total funding
$1.3B
Klaviyo (NYSE: KVYO) is the autonomous B2C CRM. Powered by its built-in data platform and AI, Klaviyo combines marketing automation, analytics, and customer service into one unified solution, making it easy for businesses to know their customers and grow faster. Klaviyo (CLAY-vee-oh) helps over 193,000 brands like Mattel, Glossier, Daily Harvest, and Liquid Death deliver 1:1 experiences at scale, improve efficiency, and drive revenue.
Offices: 125 Summer St, Floor 7, Boston, Massachusetts 02110, US · 106 Fenchurch Street, 5th Floor, London, England EC3M 5JF, GB · 420 George St, Floor 17, Sydney, NSW 2000, AU · 1615 Platte St, Denver, Colorado 80202, US · 181 Fremont St, Floor 21, San Francisco, California 94105, US
How much do Engineering jobs in Palo Alto, CA pay?
Based on 734 listings with disclosed salaries, most engineering jobs in Palo Alto, CA pay between $100k–$261k per year. Individual offers vary with seniority, company size, and specialization.
How many Engineering jobs are open in Palo Alto, CA right now?
There are currently 915 open engineering positions in Palo Alto, CA listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Engineering roles in Palo Alto, CA?
Companies currently hiring include Rivian, Ford Motor Company, SpaceX, Rivian and Volkswagen Group Technologies, Amazon, among others. Browse the listings above to see every active employer.
Are there remote or hybrid Engineering jobs in Palo Alto, CA?
Yes — 385 of the 915 open engineering positions offer remote or hybrid work (56 remote, 329 hybrid).
How do I apply for Engineering jobs in Palo Alto, CA?
Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.