Senior Machine Learning Scientist (Recommender Systems) Job at Tripadvisor

Senior Machine Learning Engineer

As Babylist’s Senior Machine Learning Engineer, you’ll be the founding expert dr...

Location

United States; Canada

Salary:

189900.00 - 237400.00 USD / Year

Babylist

Expiration Date

Until further notice

Requirements

6+ years of experience delivering end to end solutions that drive business growth
Deep expertise in the Python ML ecosystem (pandas, sklearn, xgboost, PyTorch)
Strong expertise creating custom embeddings from raw data sources
Experience going beyond off-the-shelf image/text embeddings to develop domain-specific representations for ML models
Proven track record building and delivering production-grade ML solutions, especially recommender systems or personalization features
Experience with the entire ML lifecycle, including workflow orchestration (Airflow) and model monitoring
Strong communication skills with technical and non-technical stakeholders
Background in consumer-facing products preferred
Expertise with e-commerce, dating apps, or complex user journey platforms is highly relevant
Demonstrate autonomy: able to define problem space, architect solutions from scratch (zero to one), and operate with ownership

Job Responsibility

Pioneer ML at Babylist: shape the roadmap, practices, and culture for machine learning and personalization at scale
Own high-impact work end-to-end: build and launch high-leverage personalization features from the ground up
Lead both technically and strategically: be the technical pioneer and strategic leader for ML at Babylist
Collaborate across a strong data organization: partner with data scientists, data engineers, and analytics engineers

What we offer

Competitive salary with equity and bonus opportunities
Company-paid medical, dental, and vision insurance
Retirement savings plan with company matching and flexible spending accounts
Generous paid parental leave and PTO
Remote work stipend to set up your office
Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

Fulltime

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

Senior Data Scientist

Are you brimming with fresh ideas to lead our Data Science team in providing dat...

Location

Belgium , Diegem

Salary:

Not provided

Sopra Steria

Expiration Date

Until further notice

Requirements

At least 7+ years of experience in Data Science
Coordinate the development and implementation of solutions with machine and deep learning at our customers
Assess the quality and performance of existing predictive models
Lead a team of talented Data Scientists
Master's degree (or equivalent through experience) in a field that is highly data-driven
Experience with some of the following data science techniques: supervised and unsupervised learning models, deep learning, anomaly detection, recommender systems, natural language processing, computer vision and reinforcement learning
Experience in one of the following languages: Python, R, Spark, Scala, Java or C++
Extensive experience in building and implementing advanced analytics solutions backed up with some reference cases
Well versed in open-source software and libraries in Python and/or R for machine and deep learning
Experience with big data and platforms such as Azure Machine Learning Services and Amazon SageMaker is a plus

Job Responsibility

Lead our Data Science team in providing data-driven solutions to our customers based on the latest machine learning models and deep learning algorithms
Apply skills to real scenarios and in different domains, such as drug discovery in healthcare, fraud detection in banks, the development of recommendation systems in the retail sector, and more

What we offer

Mobility options (including a company car), insurance coverage, meal vouchers, eco-cheques, and more
Continuous learning opportunities through the Sopra Steria Academy
The opportunity to connect with fellow Sopra Steria colleagues at various team events

Fulltime

Senior Data Scientist

Location

India , Bengaluru

Salary:

Not provided

ADM

Expiration Date

Until further notice

Requirements

Bachelor's degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field. Master’s degree or Ph.D. is a plus
7+ years of experience in data science, machine learning, or AI, with demonstrated success in building models that drive business outcomes
Proficient in Python, R, and SQL for data analysis, modeling, and data pipeline development
Experience with DevSecOps practices, and tools such as GitHub, Azure DevOps, Terraform, Bicep, AquaSec etc
Experience with cloud platforms (Azure, AWS, Google Cloud) and large-scale data processing tools (e.g., Hadoop, Spark)
Strong understanding of both supervised and unsupervised learning models and techniques
Experience with frameworks like TensorFlow, PyTorch, and working knowledge of Generative AI models like GPT and GANs
Hands-on experience with Generative AI techniques, but with a balanced approach to leveraging them where they can add value
Proven experience in rapid prototyping and ability to iterate quickly to meet business needs in a dynamic environment

Job Responsibility

Lead end-to-end machine learning projects, from data exploration, modeling, and deployment, ensuring alignment with business objectives
Utilize traditional AI/data science methods (e.g., regression, classification, clustering) and advanced AI methods (e.g., neural networks, NLP) to address business problems and optimize processes
Implement and experiment with Generative AI models based on business needs using Prompt Engineering, Retrieval Augmented Generation (RAG) or Finetuning, using LLM's, LVM's, TTS etc
Collaborate with teams across Digital & Innovation, business stakeholders, software engineers, and product teams, to rapidly prototype and iterate on new models and solutions
Mentor and coach junior data scientists and analysts, fostering an environment of continuous learning and collaboration
Adapt quickly to new AI advancements and technologies, continuously learning and applying emerging methodologies to solve complex problems
Work closely with other teams (e.g., Cybersecurity, Cloud Engineering) to ensure the successful integration of models into production systems
Ensure models meet rigorous performance, accuracy, and efficiency standards, performing cross-validation, tuning, and statistical checks
Communicate results and insights effectively to both technical and non-technical stakeholders, delivering clear recommendations for business impact
Ensure adherence to data privacy, security policies, and governance standards across all data science initiatives

Senior Applied Scientist

PagerDuty, Inc. (NYSE:PD) is a global leader in digital operations management. H...

Location

Portugal , Lisbon

Salary:

Not provided

PagerDuty

Expiration Date

Until further notice

Requirements

Graduate degree in computer science, statistics, mathematics, or related quantitative field
7+ years using machine learning and statistical analysis for building data-driven product solutions for large scale systems
Hands on experience in python, SQL and other related tools
Have an entrepreneurial mindset to drive research projects to completion with minimal guidance
Strong ability to justify technical prioritization and communicate scientific work in a clear and effective manner stakeholders, other engineers and Product
Experience working with Engineering teams ensuring a timely delivery

Job Responsibility

Build production-grade ML models and AI-powered solutions to business critical challenges across multiple domains on top of PagerDuty’s data infrastructure
Work both independently and collaboratively with other applied scientists, product managers, engineers, and designers to solve complex problems that deliver business value
Influence leadership and stakeholders to drive more data-informed decisions and to identify impactful AI use-cases across our products
Communicate, align and drive interest within the entire organization to be more data driven
Provide guidance, enablement, technical leadership, and mentorship to other members of the organization
Lead research initiatives using generative AI, agents and traditional ML techniques
Proactively recommend improvements and new approaches to ensure continuous improvement across our existing models and services and tackling technical debt

What we offer

Competitive salary
Comprehensive benefits package from day one
Flexible work arrangements
Company equity
ESPP (Employee Stock Purchase Program)
Retirement or pension plan
Generous paid vacation time
Paid holidays and sick leave
Dutonian Wellness Days & HibernationDuty - companywide paid days off in addition to PTO
Paid parental leave: 22 weeks for pregnant parent, 12 weeks for non-pregnant parent (some countries have longer leave standards and we comply with local laws)

Fulltime

Senior People Scientist

The Sr People Scientist is responsible for supplying to the development of an en...

Location

United States , Bellevue

Salary:

127700.00 - 230300.00 USD / Year

T-Mobile

Expiration Date

Until further notice

Requirements

Bachelor's Degree Quantitative Subject area (math, statistics, economics, computer science, physics, engineering)
Master's/Advanced Degree Quantitative Subject area (I-O Psychology
Behavioral Economics
Applied Social Psychology w/emphases on research science and advanced statistics)
Doctorate Quantitative Discipline (I-O Psychology
Behavioral Economics
Applied Social Psychology w/emphases on research science and advanced statistics)
7-10 years Research science or related experience
Proven experience with Gen AI for foundational models and LLM and demonstrating for analytics
4-7 years Combination of deep technical skills and business savvy to interface and influence all levels and fields

Job Responsibility

Support the vision and research science roadmap in collaboration with the HR leadership team and senior leadership partners
Collaborate in identifying and addressing large-scale, sophisticated business problems related to employee experience, talent, and organizational capability
Drive the development and integration of diverse and complex data sources for advanced and sophisticated qualitative and quantitative modeling
Contribute to maintaining high standards in research science, including supporting the mentoring and development of team members
Develop and implement network analytics, AI/ML, and Deep Learning models to analyze sophisticated datasets and support innovation in people science
Build and run true A/B and quasi-experimental designs to assess the impact of mechanisms, programs, and various tested solutions that align to the overall T-Mobile people strategy
evaluate research initiatives to provide bottom line value, return on investment and improvements
Translate technical research findings into clear, concise, and engaging reports that support decisions and applications across the employee lifecycle
Collaborate with multiple teams and account teams to influence, build consensus, and drive significant T-Mobile wide changes related to applying research science proposals and recommendations, including changes to programs, engineering and system needs, and people strategy roadmaps

What we offer

medical, dental and vision insurance
flexible spending account
401(k)
employee stock grants
employee stock purchase plan
paid time off
up to 12 paid holidays
paid parental and family leave
family building benefits
back-up care

Fulltime

Lead Scientist, Pricing

We are seeking a Lead Data Scientist with deep expertise in pricing science, inc...

Location

United States

Salary:

Not provided

Duetto

Expiration Date

Until further notice

Requirements

MS or PhD in Statistics, Econometrics, Computer Science, Operations Research, or a related quantitative field
7+ years of hands-on experience building data science solutions for pricing, decision-making, or control systems
Demonstrated success applying reinforcement learning in production settings, ideally in pricing or dynamic decision environments
Proficiency with ML/DL frameworks (e.g., PyTorch, TensorFlow, scikit-learn, DARTS) and programming languages (Python, R, SQL)
Experience with Python-based libraries for mathematical optimization and reinforcement learning, and familiarity with simulation environments for offline policy evaluation
Familiarity with cloud platforms and MLOps tools (e.g., AWS SageMaker, MLflow) for scalable model development and deployment
Strong communication and presentation skills, capable of conveying complex analytical concepts to non-technical stakeholders
Experience designing model evaluation and impact measurement frameworks, including causal inference

Job Responsibility

Lead the development of intelligent pricing systems using reinforcement learning, constrained optimization, and simulation-based approaches
Apply a combination of mathematical optimization, dynamic programming, and advanced reinforcement learning algorithms (e.g., model-free, policy gradients, model-based RL) to develop adaptive pricing strategies at scale
Incorporate price elasticity modeling, demand forecasts, and business constraints into the optimization framework
Build and validate simulation environments to evaluate policies offline and ensure robustness before production deployment
Collaborate with engineering to productionize and monitor models in cloud environments such as AWS SageMaker
Collaborate with engineering to productionize optimization models via batch or real-time pricing APIs (e.g., using AWS SageMaker)
Partner with product, pricing, and revenue strategy teams to define objectives and translate pricing insights into business outcomes
Define and execute model performance measurement strategies, including causal inference and uplift modeling and A/B testing
Present findings, experimental results, and strategic recommendations to senior leadership

Associate Director, Reinforcement Learning (ML)

Lead Amgen’s strategy and execution for Reinforcement Learning from Human Feedba...

Location

United States , Thousand Oaks; Jacksonville

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Doctorate degree and 3 years of Computer Science, IT or related field experience
Master’s degree and 5 years of Computer Science, IT or related field experience
Bachelor’s degree and 7 years of Computer Science, IT or related field experience
Associate’s degree and 12 years of Computer Science, IT or related field experience
High school diploma / GED and 14 years of Computer Science, IT or related field experience
Deep, hands-on expertise in Reinforcement Learning from Human Feedback (RLHF) and/or advanced reinforcement learning, including reward modeling, policy optimization, exploration strategies, and offline/online evaluation
Demonstrated experience deploying RLHF or RL systems into production for real-world applications (e.g., large language models, recommendation systems, decision support tools, or workflow automation), ideally in healthcare, life sciences, or other regulated domains
Strong background in modern machine learning and deep learning, with practical experience in Python and frameworks such as PyTorch or TensorFlow, and familiarity with LLM ecosystems and tooling
Experience driving sophisticated, cross-functional initiatives, collaborating with non-technical stakeholders (e.g., physicians, scientists, commercial leaders, compliance, legal) and translating needs into impactful AI solutions
Strong ability to communicate complex technical topics simply, tailoring content to senior executives and non-technical audiences

Job Responsibility

Lead the design and development of RLHF systems including reward modeling, policy optimization, safety and alignment mechanisms, and evaluation frameworks for large language models and other AI systems
Drive hands-on technical execution, particularly for high-impact projects, reviewing architectures, experimentation plans, and code, and helping the team navigate scientific and engineering trade-offs
Establish best-practice pipelines for human feedback, partnering closely with internal customer teams to define feedback protocols, annotation quality standards, and governance for RLHF data
Define and track success metrics for RLHF systems, balancing offline and online evaluation, A/B tests, safety and robustness criteria, and business or scientific outcomes
Collaborate across Amgen leaders to ensure RLHF solutions are aligned with strategy, compliant with policy, and integrated into real workflows
Partner with Data, Platform and Technology teams to ensure that RLHF workloads are supported by scalable data platforms, model hosting, experimentation infrastructure, and MLOps best practices
Champion responsible and compliant AI, working with Legal, Compliance, and Information Security to implement governance around human feedback, data usage, model behavior, transparency, and risk management in a regulated environment
Communicate insights and influence senior stakeholders, creating clear narratives, roadmaps, and recommendations that help executives understand RLHF trade-offs, risks, and opportunities

What we offer

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible

Senior Machine Learning Scientist (Recommender Systems)

Tripadvisor

Location:

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 07, 2026

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