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

Principal Applied Scientist

The Core Recommendation Ranking team in Microsoft AI Copilot Discover Engineerin...

Location

United States , Redmond

Salary:

139900.00 - 304200.00 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 (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
8+ years of experiences in applied science, deep learning, or related fields, with a solid track record of delivering production ML systems at scale
Expertise in recommendation systems, ranking models, search relevance, or personalization
Experience applying LLM techniques or Recommendation system

Job Responsibility

Design & implement ranking, reranking, and retrieval models using deep learning, LLMs, and advanced recommendation techniques
Architect the next generation of ranking, reranking, and retrieval systems for large-scale content recommendation scenarios
Lead the design of robust, efficient, and extensible ML/DL models pipelines
Drive innovation in model architectures
Partner with engineering, product, and platform teams to align roadmaps
Invest in others' growth and mentor team members
Regularly communicate team progress internally and evangelize progress
Mentor junior scientists and engineers

What we offer

Benefits and other compensation
https://careers.microsoft.com/us/en/us-corporate-pay

Fulltime

Principal Applied Scientist

The Core Recommendation Ranking team in Microsoft AI Content Org is looking for ...

Location

United States , Redmond

Salary:

163000.00 - 296400.00 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 8+ 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 6+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience
OR equivalent experience
Expertise in recommendation systems, ranking models, search relevance, or personalization
Experience applying LLM techniques or Recommendation system
Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow), data processing systems, and cloud‑scale infrastructure
Demonstrated ability to lead cross‑functional initiatives and influence technical direction across multiple teams
Solid communication skills with the ability to articulate complex technical concepts to diverse audiences

Job Responsibility

Architect the next generation of ranking, reranking, and retrieval systems for large‑scale content recommendation scenarios
Lead the design of robust, efficient, and extensible ML/DL models pipelines, including feature engineering, model training, evaluation, and online inference
Establish technical standards and best practices for experimentation, model governance, and system reliability
Drive innovation in model architectures (e.g., deep learning, LLM‑enhanced ranking, multi‑task learning, contextual bandits, reinforcement learning)
Partner with engineering, product, and platform teams to align roadmaps, integrate new capabilities, and ensure seamless end‑to‑end delivery
Invest in others’ growth and mentor team members, fostering a culture of scientific rigor, innovation, and operational excellence
Regularly communicate team progress internally and evangelize progress and opportunities to a wider audience including management and leadership

Fulltime

Applied Scientist, AWS Marketplace & Partner Services

The AWS Marketplace team is looking for an Applied Scientist to help build and i...

Location

United States , Seattle

Salary:

142800.00 - 193200.00 USD / Year

Amazon

Expiration Date

Until further notice

Requirements

Experience programming in Java, C++, Python or related language
PhD in computer science, machine learning, engineering, or related fields
3+ years of building machine learning models or developing algorithms for business application experience

Job Responsibility

Design, develop, and deploy AI/ML models for search ranking, query understanding, recommendation, and discovery systems
Develop and improve information retrieval systems that operate over complex product taxonomies, knowledge graphs, and structured/unstructured metadata
Build relevance models that capture nuanced relationships between customer intent, product capabilities, and domain-specific context
Advance both traditional discovery experiences (search, browse, personalized recommendations) and agentic discovery with multi-agent systems
Conduct experiments and A/B tests to measure and improve the relevance and performance of discovery features
Analyze large-scale datasets to identify patterns, generate insights, and inform model development
Collaborate with engineers and product managers to integrate AI/ML solutions into production systems
Stay current with relevant research in information retrieval, knowledge representation, NLP, and recommendation systems, and apply findings to improve our systems

What we offer

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

Fulltime

Principal Applied Scientist

In Feeds and AI team, we’re building Microsoft Start, a content powerhouse for e...

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
Minimum of 3 years of professional experience in recommender systems, search engines, or online advertising
Strong expertise in machine learning algorithms, generative AI and statistics, and data mining techniques applied to personalization
Proven problem-solving abilities and a track record of thriving in fast-paced, collaborative environments
Excellent communication and teamwork skills, with the ability to clearly articulate complex technical concepts to a variety of audiences
Proficient in Python programming
Additional experience in languages such as C# or C++ considered 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 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

Senior Applied Scientist

In Feeds and AI team, we’re building Microsoft Start, a content powerhouse for e...

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 4+ 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 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
Minimum of 3 years of professional experience in recommender systems, search engines, or online advertising, with strong expertise in machine learning algorithms, generative AI and large language models (LLMs), statistics, and data mining techniques applied to personalization.
Proven problem-solving abilities and a track record of thriving in fast-paced, collaborative environments.
Excellent communication and teamwork skills, with the ability to clearly articulate complex technical concepts to a variety of audiences.
Proficient in Python programming, with additional experience in languages such as C# or C++ considered 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 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

Machine Learning Engineer

FOX Corporation is looking for a SDE (L2), ML / Senior Engineer, ML to join the ...

Location

India , Bengaluru

Salary:

Not provided

Fox News Media

Expiration Date

Until further notice

Requirements

At least 3-7 years of experience in machine learning, applied data science, or related fields, with a strong focus on recommendation systems or personalization
Demonstrated experience in developing and deploying ML models into production environments
Deep understanding of ranking systems, user behavior modeling, and evaluation techniques (e.g., NDCG, AUC, MAP, CTR)
Proficient in Python and ML libraries like PyTorch, TensorFlow, and frameworks such as Transformers or LightGBM
Experience with Databricks, Spark, or similar big data platforms for large-scale model training and data processing
Familiarity with model versioning, feature stores, experiment tracking, and MLflow
Strong grasp of A/B testing design, analysis, and interpreting results for iterative model improvements
Experience with LLM-based pipelines, semantic search, or vector similarity systems (e.g., FAISS, Vespa) is a plus
Comfort working in cloud-native environments such as AWS or GCP

Job Responsibility

Design and build scalable recommendation and personalization models (ranking, re-ranking, user embeddings, semantic retrieval)
Own the full model lifecycle: from data preparation, training, and evaluation, to versioning, deployment, and monitoring
Develop and maintain continuous training loops and model refresh strategies for dynamic personalization
Set up and interpret A/B experiments to optimize model performance and user engagement
Collaborate with data engineers, MLOps teams, and product managers to ensure models integrate seamlessly into real-time and batch inference pipelines
Leverage platforms like Databricks, MLflow, and feature stores to streamline model experimentation and reproducibility
Apply LLMs and AI agents to improve personalization workflows and accelerate ML development pipelines
Contribute to architecture decisions for personalization services and model serving infrastructure
Mentor and provide technical guidance to junior data scientists and ML engineers, conducting code reviews, sharing best practices, and supporting their growth in areas such as model development, experimentation, and productionization

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

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Applied Scientist - Personalization and Recommendation

Job Description

Job Responsibility

Requirements

What we offer

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