Applied Scientist - Personalization and Recommendation Job at OnePay

Senior Machine Learning Engineer, Personalization and Recommendations

As a Senior Machine Learning Engineer on the Personalization & Recommendations t...

Location

United States , San Francisco

Salary:

183360.00 - 248000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems
Demonstrated impact improving key metrics such as CTR, retention, or engagement through recommender or search systems in production
Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices — including model registries, feature stores, monitoring, and drift detection
Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, or MMoE, and the ability to apply them to real-world problems
Experience with large-scale embedding models and vector search, including FAISS, ScaNN, or similar systems
Proficiency in experiment design and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B test outcomes to drive product decisions
Clear, effective communication, collaborating well with product managers, data scientists, engineers, and cross-functional partners
A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability
Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals

Job Responsibility

Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals and content features
Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization
Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training–serving consistency, observability, and robust monitoring
Partner with Product and Data Science to translate learner objectives (engagement, retention, mastery) into measurable modeling goals and experiment designs
Advance evaluation methodologies, contributing to offline metric design (e.g., NDCG, CTR, calibration) and supporting rigorous A/B testing to measure learner and business impact
Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments
Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem
Mentor junior and mid-level engineers, supporting technical growth, experimentation rigor, and responsible ML practices
Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture

What we offer

20 vacation days
Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
Employer-sponsored 401k plan with company match
Access to LinkedIn Learning and other resources to support professional growth
Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
40 hours of annual paid time off to participate in volunteer programs of choice

Fulltime

Research Engineer, GenAI

You will be part of Kiddom’s Data Science team, building the foundation of our s...

Location

United States , San Francisco; New York

Salary:

175000.00 - 250000.00 USD / Year

Kiddom

Expiration Date

Until further notice

Requirements

5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets
1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python
Fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

What we offer

Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State
Commuter and FSA plans

Fulltime

Machine Learning Research Engineer

You will be part of Kiddom’s Data Science team, building the foundation of our s...

Location

United States , San Francisco; New York

Salary:

175000.00 - 250000.00 USD / Year

Kiddom

Expiration Date

Until further notice

Requirements

Have 5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets, with 1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

What we offer

Competitive salary
Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State
Commuter and FSA plans

Fulltime

New

Senior Machine Learning Engineer

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Menlo Park, CA; Bellevue, WA

Salary:

209000.00 - 245000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

5+ years of applied ML experience productionizing ML models with 2+ years focused on recommendations, ranking or personalization projects
A fervent interest in exploring and applying AI and ML technologies
Strive to solve sophisticated engineering problems that drive business objectives
Solid technical foundation enabling active contribution to the design and execution of projects and ideas
Familiarity with architectural frameworks of large, distributed, and high-scale ML applications
Hands-on experience in classical ML techniques with tabular data as well as modern techniques with sequential data
Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning
Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow
Experience with Spark, Kafka, and Kubernetes is also desirable
Ideally you have experience in the Finance sector

Job Responsibility

AI and ML Research: Evaluate cutting technologies, including but not limited to, transformer based model architecture and large foundational models to identify solutions for Robinhood specific problems
Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content-Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation
A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results
Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy
Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to different stakeholders
Tooling and Documentation: Build reusable libraries for common machine learning practices. Offer support and guidance to the usage of these tools. Maintain comprehensive documentation of libraries, models, experiments, and findings

What we offer

Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces

Fulltime

Senior Machine Learning Engineer

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Menlo Park; Bellevue

Salary:

187000.00 - 220000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

5+ years of applied ML experience productionizing ML models with 2+ years focused on recommendations, ranking or personalization projects
A fervent interest in exploring and applying AI and ML technologies
Strive to solve sophisticated engineering problems that drive business objectives
Solid technical foundation enabling active contribution to the design and execution of projects and ideas
Familiarity with architectural frameworks of large, distributed, and high-scale ML applications
Hands-on experience in classical ML techniques with tabular data as well as modern techniques with sequential data
Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning
Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow

Job Responsibility

AI and ML Research: Evaluate cutting technologies, including but not limited to, transformer based model architecture and large foundational models to identify solutions for Robinhood specific problems
Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content-Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation
A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results
Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy
Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to different stakeholders
Tooling and Documentation: Build reusable libraries for common machine learning practices. Offer support and guidance to the usage of these tools. Maintain comprehensive documentation of libraries, models, experiments, and findings

What we offer

Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces

Fulltime

New

Principle Applied Scientist

In Feeds and AI team, we’re building Microsoft Copilot Discover, a content power...

Location

China , Beijing

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience OR equivalent experience
3 years of work experience in recommender systems, search engine, or online advertising, with rich experience on machine learning algorithms, generative AI / advanced AI solution, statistics, data mining techniques, and their application on personalization
Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment
Strong communication and teamwork skills, with the ability to effectively present and explain technical concepts to diverse audiences
Strong programming skills in Python and experience with other programming languages like C#, C++ is a plus

Job Responsibility

Algorithm Development and Enhancement for ranking algorithms in News & Feeds
Work with cross-functional teams to design, develop, and implement recommendation algorithms to deliver product features and drive user engagement
Optimize existing recommendation algorithms by analyzing performance metrics and user feedback, incorporating advanced machine learning techniques including generative AI techniques
Innovation in the area of NLP, advanced AI solution, and recommender system
Perform data analysis to identify patterns, trends, and opportunities to improve the relevance and quality of our recommendation systems
Build systemic solutions and models to optimize user experience

Fulltime

Principal Applied Scientist

As a Principal Applied Scientist at Viva Engage, your role is to build Agentic a...

Location

United States , Mountain View

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter

Job Responsibility

Design, build, and ship machine learning and LLM-driven capabilities that directly power AI features in Viva Engage, with clear product KPIs (e.g., activation, retention, engagement, moderation quality, time saved)
Own end-to-end delivery of applied science solutions: problem framing → data/labels → modeling/prompting → evaluation → experimentation (A/B tests) → deployment → monitoring → iteration
Develop and operationalize AI agents for knowledge discovery, moderation, communities, and events—focused on measurable user value, automation, and high-quality recommendations
Work with large, complex datasets to solve ambiguous, non-routine product problems using advanced statistical and ML methods, prioritizing approaches that are production-viable
Utilize Large Language Models (LLMs) for advanced text analysis and natural language understanding tasks, enabling deeper connections and knowledge sharing across organizations
Leverage generative AI techniques to enhance data augmentation and predictive capabilities, further improving recommendations and personalized user experiences
Develop deep product intuition to influence future product roadmaps and drive decision-making by making pragmatic tradeoffs between model quality, engineering complexity, and time-to-value
Collaborate with product and engineering to craft experiments and test hypotheses
Communicate clearly across disciplines: translate complex technical decisions into product implications, risks, and expected outcomes
Operate effectively in complex, cross-team environments and drive alignment through technical leadership and execution

Fulltime

Manager, Data Science

We’re looking for a Data Science Manager to architect and lead the next generati...

Location

United States , San Francisco

Salary:

187000.00 - 281000.00 USD / Year

GoFundMe

Expiration Date

Until further notice

Requirements

8+ years of experience in data science roles with direct impact on marketing, growth, or revenue optimization
Master’s or Ph.D. in a quantitative field (Statistics, Mathematics, Economics, Computer Science, Physics, Operations Research or related), or equivalent applied experience
Advanced proficiency in Python (NumPy, pandas, scikit-learn) and SQL (window functions, optimization)
Deep experience with experimentation frameworks: A/B testing, causal inference, uplift modeling, and attribution models
Proven success in forecasting, optimization, and budget allocation models for marketing and growth functions
Hands-on with data platforms (Snowflake, Databricks) and BI tools (Looker, Tableau, or equivalent)
Strong data storytelling and executive presentation abilities
Exceptional communication skills with the ability to influence executive stakeholders and translate data into actionable business recommendations
Experience developing senior data scientists and elevating team practices
Demonstrated ability to define a strategic vision for applied data science in marketing, balancing rapid experimentation with long-term infrastructure investments

Job Responsibility

Build a strong AI and data science foundation: Develop scalable pipelines, reusable modeling frameworks, and robust experimentation platforms to support marketing and growth decision-making
Lead end-to-end data science & AI projects: From requirements gathering through feature engineering, modeling, validation, deployment, and monitoring
Establish best practices: Champion standards in model governance, reproducibility, data quality, and system reliability to ensure sustainable and trustworthy AI adoption
Drive marketing science innovation: Apply advanced methods—causal inference, uplift modeling, multi-touch attribution, and media mix modeling—to unlock insights and optimize spend
Advance forecasting & ROI modeling: Deliver budget allocation frameworks and predictive models that guide long-term roadmap planning and marketing efficiency
Partner cross-functionally: Work closely with Marketing, Growth, Product, Engineering, and Finance leaders to align analytics initiatives with revenue impact
Invest in people: Mentor, coach, and elevate a team of high-performing data scientists
foster a culture of technical rigor, curiosity, and applied innovation
Push the frontier of applied AI in marketing: Evaluate emerging generative and predictive AI approaches for audience segmentation, creative optimization, personalization, and campaign efficiency

What we offer

Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year
Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere
Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together
Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits
Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being
Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow
Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups
Community Engagement: Make a difference through our volunteering program

Fulltime

Applied Scientist - Personalization and Recommendation

OnePay

Location:
United States

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
February 21, 2026

Looking for more opportunities? Search for other job offers that match your skills and interests.

Similar Jobs for Applied Scientist - Personalization and Recommendation