Product Data Scientist, Search Quality Job at Perplexity (Belgrade, London, Berlin)

Senior Data Scientist

We are seeking a Senior Data Scientist with deep expertise in unstructured data ...

Location

Salary:

Not provided

Beyond Limits

Expiration Date

Until further notice

Requirements

5+ years of hands-on experience in AI, Machine Learning, and Data Science, with a strong focus on production-scale AI
Expertise in LLMs, including fine-tuning, distributed training, quantization, and pruning techniques
Experience working with OCR, ASR, and TTS applications in real-world deployments
Proven experience deploying AI models in production, with real-world examples of scaled AI applications
Strong understanding of cloud computing, containerization (Docker, Kubernetes), and ML Ops best practices
Proficiency in Python, PyTorch, and ML libraries
Hands-on experience with vector databases and retrieval-augmented generation (RAG) architectures
Strong awareness of AI system performance benchmarks (latency, speed, throughput) and ability to optimize models accordingly
Experience working with AI agents, designing real-world intelligent automation solutions beyond just open-source experimentation
Proficiency in transformer-based architectures (BERT, GPT, LLaMA, Whisper, etc.), including pre-training, fine-tuning, and task-specific adaptation

Job Responsibility

Develop and deploy AI models for unstructured data (text, speech, audio, images) with a focus on enterprise-scale performance
Fine-tune, optimize, and deploy LLMs and multimodal models, integrating distributed training, quantization, and pruning techniques for efficiency
Design and implement production-ready AI solutions, ensuring scalability, low-latency inference, and high throughput
Work with AI agents and automation frameworks to create intelligent, real-world AI applications for enterprise clients
Build and maintain end-to-end LLM Ops pipelines, ensuring efficient training, deployment, monitoring, and model updates
Implement vector search and retrieval-augmented generation (RAG) systems for large-scale data solutions
Monitor AI performance using key metrics such as speed, latency, and throughput, continuously refining models for real-world efficiency
Work with cloud-based AI infrastructure (AWS, GCP) and containerized environments (Docker, Kubernetes) to scale AI solutions
Collaborate with engineering, DevOps, and product teams to align AI solutions with business needs and client requirements
Implement data curation pipelines, including data collection, cleaning, deduplication, decontamination, etc. for training high-quality AI models

Senior Data Scientist

We are seeking a Senior Data Scientist with deep expertise in unstructured data ...

Location

Taiwan

Salary:

Not provided

Beyond Limits

Expiration Date

Until further notice

Requirements

5+ years of hands-on experience in AI, Machine Learning, and Data Science, with a strong focus on production-scale AI
Expertise in LLMs, including fine-tuning, distributed training, quantization, and pruning techniques
Experience working with OCR, ASR, and TTS applications in real-world deployments
Proven experience deploying AI models in production, with real-world examples of scaled AI applications
Strong understanding of cloud computing, containerization (Docker, Kubernetes), and ML Ops best practices
Proficiency in Python, PyTorch, and ML libraries
Hands-on experience with vector databases and retrieval-augmented generation (RAG) architectures
Strong awareness of AI system performance benchmarks (latency, speed, throughput) and ability to optimize models accordingly
Experience working with AI agents, designing real-world intelligent automation solutions beyond just open-source experimentation
Proficiency in transformer-based architectures (BERT, GPT, LLaMA, Whisper, etc.), including pre-training, fine-tuning, and task-specific adaptation

Job Responsibility

Develop and deploy AI models for unstructured data (text, speech, audio, images) with a focus on enterprise-scale performance
Fine-tune, optimize, and deploy LLMs and multimodal models, integrating distributed training, quantization, and pruning techniques for efficiency
Design and implement production-ready AI solutions, ensuring scalability, low-latency inference, and high throughput
Work with AI agents and automation frameworks to create intelligent, real-world AI applications for enterprise clients
Build and maintain end-to-end LLM Ops pipelines, ensuring efficient training, deployment, monitoring, and model updates
Implement vector search and retrieval-augmented generation (RAG) systems for large-scale data solutions
Monitor AI performance using key metrics such as speed, latency, and throughput, continuously refining models for real-world efficiency
Work with cloud-based AI infrastructure (AWS, GCP) and containerized environments (Docker, Kubernetes) to scale AI solutions
Collaborate with engineering, DevOps, and product teams to align AI solutions with business needs and client requirements
Implement data curation pipelines, including data collection, cleaning, deduplication, decontamination, etc. for training high-quality AI models

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 Modeler

We are seeking a visionary Senior Data Modeler to architect the backbone of our ...

Location

Salary:

Not provided

Coca-Cola HBC

Expiration Date

Until further notice

Requirements

BSc or MSc in relevant fields such as Computer Science, Information Science, Data Science, Artificial Intelligence, Knowledge Engineering, Computational Linguistics, or related discipline
2+ experience in Data Architecture, Semantic Architecture, Knowledge Architecture, Data Integration and Metadata Management
Data Vault 2.0, Dimensional Modeling (Kimball), 3NF, Strong understanding of one or more of the following: Knowledge Models, knowledge graphs, metadata storage, versioning, tagging and modelling
Experience with automated metadata management and lineage tools
Advanced SQL, Python (for metadata automation) / PySpark, and SPARQL/Cypher
Hands-on experience designing data architecture patterns to support RAG pipelines, prompt / grounding patterns, context orchestration and memory management
Understanding of how structured data feeds into Vector DBs and LLM contexts
Systems Thinking: Ability to see the "Big Picture" and how one change impacts the entire network
Acting as the bridge between the "Data Producers" (Engineers) and "Data Consumers" (Data Scientists)
Experience with relevant technologies such as graph databases, vector / search platforms, semantic web technologies, event-based streaming platforms, and cloud AI / data ecosystems

Job Responsibility

Design and implement a robust Hub-and-Spoke data model (e.g., Data Vault 2.0 or specialized Star Schema) to decouple core business entities from source-specific attributes
Establish "Golden Records" within the Hub to ensure a single version of truth for master data (Customer, Product, Asset)
Standardize "Spoke" delivery layers to provide high-performance, domain-specific data marts for downstream AI/ML consumption
Design data structures for event-based, streaming integration patterns including structured and unstructured data
Develop and maintain the Semantic Layer to abstract complex SQL logic into business-friendly terms
Map data relationships into an Ontology/Knowledge Graph format to support RAG (Retrieval-Augmented Generation) and AI reasoning
Define the logic for metrics, attributes, and hierarchies once, ensuring consistency across all AI agents and BI tools
Integrate data models with an Enterprise Data Catalog (e.g., Atlan, Purview)
Automate metadata harvesting to ensure the catalog reflects real-time lineage, quality scores, and ownership
Tag data with semantic descriptors to enable AI-driven "natural language to SQL" capabilities

What we offer

Coaching and mentoring programs
Development opportunities
Equal opportunity employer
IT Equipment
Work with iconic brands
Supportive team

Senior Applied Scientist - Image & Video Search Algorithm

Are you interested in solving large‑scale search problems and building next‑gene...

Location

China , Beijing

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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
Proven track record of impact in search engines or recommendation systems
Solid understanding of search engine fundamentals, including query, user, and content understanding, retrieval / recall architectures, ranking and relevance optimization
Experience building production machine learning systems, from data modeling to online deployment
Hands‑on experience in one or more of the following areas: Information retrieval, Recommendation systems, Computer vision or video understanding, Deep learning, NLP, or multimodal learning
Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
Solid communication and collaboration skills in cross‑functional, global teams
MS or PhD in Computer Science or a related field

Job Responsibility

Design, develop, and improve large‑scale image and video search algorithms, with a focus on retrieval, recall, ranking, and relevance optimization
Build and operate multi‑stage search pipelines that power production image and video search experiences
Develop LLM‑powered search APIs and applications, integrating large language models with search, retrieval, and ranking systems to enable new developer and user experiences
Apply machine learning, deep learning, multimodal models, and LLM techniques to improve search quality, engagement, and long‑term product growth
Own the end‑to‑end machine learning lifecycle: Problem formulation and metric definition, Offline training, evaluation, and optimization, Online experimentation (A/B testing), Production deployment and monitoring
Build billion‑scale, low‑latency ML systems integrated into Bing and Windows search runtimes
Collaborate with researchers and partner teams to explore and productionize state‑of‑the‑art techniques for image, video, and LLM‑driven search scenarios

Principal Product Manager

Microsoft Teams is used by over 300 million people worldwide for meetings, chat,...

Location

India , Bangalore

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree AND 8+ years experience in product/service/program management or software development
8+ years of product management experience, with at least 3 years in search, information retrieval, or a related ML/AI-powered product area
Deep, hands-on experience with evaluation frameworks for search or AI systems
Solid understanding of IR fundamentals: ranking, relevance, query understanding, recall/precision trade-offs
Experience with LLM-era eval challenges: hallucination detection, groundedness, response quality, and human eval design for generative outputs
Demonstrated ability to work cross-functionally with applied scientists, ML engineers, and data teams
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter

Job Responsibility

Own Search Quality & Evals Strategy: Define the evaluation framework for Teams Search
Lead the design of human evaluation pipelines
Build and maintain an offline eval harness
Partner with Applied Science and engineering to translate eval signals into roadmap priorities and quality SLAs
Drive AI-Powered Search Features: Define product requirements for semantic search, hybrid retrieval, re-ranking, and Copilot-integrated search experiences in Teams
Own the PM relationship with the relevance science team
Work with the Copilot/AI team to integrate retrieval-augmented generation (RAG) patterns into Teams Search
Define Metrics and Success: Own the success metrics hierarchy for Teams Search
Instrument A/B experiments end-to-end
Build a culture of evidence-based decision making

Fulltime

Data Scientist/Engineer – Online Metrics

Perplexity serves tens of millions of users daily with reliable, high-quality an...

Location

United Kingdom; Germany; Serbia , London; Berlin; Belgrade

Salary:

Not provided

Perplexity

Expiration Date

Until further notice

Requirements

MS in a technical field or equivalent experience
4+ years of experience working as a Data Scientist, Analytics Engineer, or related role
Experience working on search, recommendation, or LLM-based products, with an emphasis on designing online metrics and analyzing A/B experiments
Strong proficiency in Python and SQL (expected to write production-grade code)
Deep knowledge of statistical analysis
Experience with Business Intelligence (BI) tools for visualization and reporting
Comfortable with agentic coding workflows and using AI-assisted development tools to iterate faster

Job Responsibility

Discover and validate online signals from user interactions that serve as reliable proxies for true answer quality
Design and implement novel online metrics to be tracked both in A/B testing and on product health dashboards, ensuring alignment with ground-truth evaluations
Analyze experimental results to validate these metrics, ensuring they accurately predict user satisfaction and drive product decisions
Build and maintain the data pipelines that calculate these metrics at scale, delivering actionable quality signals to Search, Product, and model training teams
Communicate findings and bring clarity through close collaboration with Product and Search teams
Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality

Fulltime

Applied Scientist

Do you want to be part of a team which delivers innovative products and machine ...

Location

United States , Redmond, WA

Salary:

100600.00 - 199000.00 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 2+ 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 1+ year(s) related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check

Job Responsibility

Researches and develops an understanding of tools, technologies, and methods being used in the community that can be utilized to improve M365 Copilot Chat and Search quality, performance, or efficiency
Contributes knowledge around several specialized tools/methods to support the application of business impact or serves as an expert in a deeply specialized area
Gains deep knowledge in M365 Copilot Search service and acquires knowledge of changes in industry trends and advances in applied technologies
Consults with engineers and product teams to apply the advanced concepts to M365 Copilot Search quality improvement
Collaborates to leverage data to identify pockets of opportunity to apply state-of-the-art algorithms to improve the search quality of M365 Copilot
Uses statistical analysis tools for evaluating the behaviors of deployed models and validating assumptions about the evaluation results, collaborating with other senior team members, building and communicating insights
Gains expertise in search relevance, NLP, and data-driven insights, and understands the corresponding literature and applicable research techniques
Uses understanding of approaches to identify techniques and works to create product impact
Identifies approach, and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact M365 Copilot Chat and Search quality
Participates in collaborative relationships with relevant product and business groups in Microsoft and provides expertise or technology to create business impact

Fulltime

Product Data Scientist, Search Quality

Perplexity

Location:

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 21, 2026

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