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Personalization Engineer Jobs (NOW HIRING)

McAfee

Senior MarTech Personalization Engineer

San Jose, CA · On-site

$123K - $170K/yr

... Engineer to lead the transformation of our marketing ecosystem. You won't just be maintaining tools; you will be architecting the intelligence layer that powers hyper-personalization, autonomous ...

Axos Bank

Jr. Personalization Developer

San Diego, CA · On-site

$71K - $92K/yr

About This Job Axos Bank is seeking a motivated Junior Martech Personalization Developer to join our growing Enterprise Marketing Technology team. In this role, you will be instrumental in building ...

Embryriddle

Personalization Specialist

Prescott, AZ · On-site

In addition to content creation, the Personalization Specialist is also responsible for ... engineering. Working alongside industry leaders, government agencies and innovators, they are ...

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Personalization Engineer information

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$39K

$101.8K

$137.5K

How much do personalization engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for personalization engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What is a personalization engineer?

A Personalization Engineer is a technology professional who designs, develops, and maintains systems that tailor digital experiences to individual users. They use data analysis, machine learning, and algorithms to create customized content, recommendations, or user interfaces on platforms like websites, apps, or e-commerce stores. Their goal is to improve user satisfaction and engagement by delivering relevant and personalized experiences based on user behavior and preferences.

How does a personalization engineer typically collaborate with data scientists and product teams?

Personalization Engineers work closely with data scientists to interpret user data and develop algorithms that tailor content or experiences to individual preferences. They also partner with product managers and designers to ensure that personalization features align with product goals and enhance user satisfaction. Regular cross-functional meetings and agile workflows are common, allowing engineers to quickly iterate on models and integrate feedback from various stakeholders. This collaborative environment helps ensure that personalization solutions are both technically sound and user-centric.

What are the key skills and qualifications needed to thrive as a personalization engineer, and why are they important?

To thrive as a Personalization Engineer, you need a strong background in computer science, data analysis, and machine learning, often supported by a relevant degree. Familiarity with tools and frameworks such as Python, TensorFlow, recommendation systems, and A/B testing platforms is typically required. Analytical thinking, creativity, and collaborative communication are crucial soft skills for designing personalized user experiences and working with cross-functional teams. These skills and qualities are essential for delivering impactful, data-driven personalization strategies that enhance user engagement and business outcomes.

What is the difference between Personalization Engineer vs Data Scientist?

AspectPersonalization EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; experience in personalization algorithmsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentDevelops and implements personalization features within tech teamsAnalyzes data to extract insights, often collaborating with product teams
Employer & Industry UsageTech companies, e-commerce, media platformsTech firms, finance, healthcare, research institutions

Personalization Engineers focus on building and optimizing algorithms for tailored user experiences, while Data Scientists analyze data to inform business decisions. Both roles require strong technical skills but differ in their primary focus and daily tasks.

What cities are hiring for Personalization Engineer jobs?

Cities with the most Personalization Engineer job openings:

What are popular job titles related to Personalization Engineer jobs?

For Personalization Engineer jobs, the most frequently searched job titles are:

Infographic showing various Personalization Engineer job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

Senior MarTech Personalization Engineer

San Jose, CA • On-site

McAfee
Network Security • 5 - 10K employees
Learn more about McAfeeexternal

$123K - $170K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 days ago

Job description

Role Summary
We are looking for a Senior AI Engineer to lead the transformation of our marketing ecosystem. You won't just be maintaining tools; you will be architecting the intelligence layer that powers hyper-personalization, autonomous campaign optimization, and generative creative pipelines. You will architect and lead buildout of infrastructure systems that do not merely execute pre-defined tasks but perceive context, reason through complex strategic problems, and orchestrate end-to-end workflows with minimal human intervention. We are moving from "campaign management" -a manual, administrative task-to "campaign orchestration" a strategic, supervisory role and invest in effective Human-Agent Teams.
This is a position located in the US in either San Jose, CA or Frisco, TX. You will be required to be onsite on an as-needed basis. We are only considering candidates within a commutable distance to one of the two locations and are not offering relocation assistance at this time.
Position Details
About the Role:
  • Architect Agentic Workflows: Design and deploy AI agents to automate complex marketing tasks such as cross-channel campaign orchestration and real-time lead qualification.
  • Generative Asset Pipelines: Build and maintain scalable pipelines for automated ad creative generation (text, image, and video) using LLMs and Multimodal models (Stable Diffusion, GPT-4o, Sora) while ensuring brand-safe guardrails.
  • Real-time Personalization: Implement RAG (Retrieval-Augmented Generation) systems to provide context-aware, personalized content across web, email, and SMS.
  • Build Predictive Models: Develop and productionalize ML models for high-impact marketing use cases: LTV (Lifetime Value) prediction, churn propensity, and "Next Best Action" engines.
  • MLOps & Integration: Own the end-to-end lifecycle of models, from feature engineering in SQL/Python to deployment via APIs and monitoring for data drift in production.
  • Privacy & Ethics: Ensure all AI implementations comply with global privacy standards (GDPR, CCPA) and implement "Privacy-First" AI features like differential privacy or synthetic data generation.
  • Governance: Implement robust Responsible AI frameworks to ensure that the speed of automation does not compromise the trust of the customer

About You:
  • Languages & Frameworks: Expert proficiency in Python. Deep experience with PyTorch or TensorFlow, and LLM orchestration frameworks (LangChain, LlamaIndex).
  • MarTech Ecosystem: Hands-on experience integrating AI with CDPs (HighTouch), ESPs (Braze, Iterable), or Ad Platforms (Meta Conversions API, Google Enhanced Conversions), Analytics (Adobe CJA), Customer focused websites (Javascript, Adobe Experience Manager)
  • Data Stack: Mastery of SQL and cloud data warehouses. Experience with Databricks for feature engineering is a huge plus.
  • Generative AI: Proven experience with Claude fine-tuning models (LoRA, QLoRA) and managing vector databases (Pinecone, Milvus, or Weaviate).
  • Deployment: Experience with Docker, Kubernetes, and cloud AI services (AWS SageMaker, Google Vertex AI, or Azure AI Studio).
  • Domain Expertise: Previous experience in a high-growth B2C marketing environment.
  • Experimentation Mindset: Strong understanding of Bayesian A/B testing and causal inference to measure the true uplift of AI interventions.
  • Strategic Thinking: Ability to translate vague marketing goals ("we want to increase engagement") into specific technical requirements and model objectives.
  • Customer TouchPoints: Experience developing applications or integrations with Windows, MacOS, iOS, Android ecosystems.

The Stack You'll Work With
  • Data Foundation: Databricks, HighTouch
  • AI/ML Engine: Claude, PyTorch, Hugging Face, OpenAI API, LangGraph
  • Orchestration: Airflow, Prefect, or GitHub Actions
  • Marketing Execution: Braze
  • Monitoring: Weights & Biases, Arize, or Grafana
  • Analytics: Adobe CJA

#LI-Hybrid
Company Overview
McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users' needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.
Company Benefits and Perks
We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.:
  • Bonus Program
  • 401k Retirement
  • Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage
  • Paid Parental Leave
  • Support and Community Involvement
  • 14 Paid Company Holidays
  • Unlimited Paid Time Off for Exempt Employees
  • 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.
Pay Range
The anticipated compensation for this position is USD $135,910.00/Yr. - USD $223,285.00/Yr. depending on experience and qualifications.
Job Applicant Privacy Notice
Please click here to view and download the Job Applicant Privacy Notice, which applies to all McAfee job applicants who are residents of the state of California.

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