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

Engineering Manager

Amgen is seeking an experienced Engineering Manager to lead our Search and Knowl...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Master’s degree in Computer Science, Software Engineering, or a related technical field with 8-13 years of software development experience OR Bachelor’s degree in Computer Science, Software Engineering, or a related technical field with 9-14 years of software development experience
8+ years of experience in software engineering, with 2–3 years in a leadership or managerial role
Strong expertise in search technologies (Elasticsearch, Solr, Lucene, Vespa, or similar)
Experience with NLP and ML frameworks
Strong background in data platform technologies (e.g., Spark, Kafka, Snowflake, Delta Lake, Hadoop, datbroicks, MongoDb, DynamoDb, S3 Buckets)
Experience with cloud infrastructure (AWS, Azure, or GCP), CI/CD, and containerization (Docker, Kubernetes)
Knowledge of distributed systems and large-scale data platforms (Spark, Hadoop, or cloud-native equivalents)
Strong programming skills (Python, Java, or Scala)
Strong understanding of software development principles, cloud platforms (AWS/Azure/GCP), and modern tech stacks (e.g., Java, Python, Angular, React)
Excellent communication, leadership, and problem-solving skills

Job Responsibility

Oversee the design and development of a modern, cloud-native data platform (e.g., using AWS/GCP/Azure, Snowflake, Databricks)
Oversee the design and implementation of scalable search solutions across biomedical literature, clinical trial data and internal knowledge repositories
Drive improvements in ranking, query understanding, entity extraction, and semantic search tailored to biomedical and life sciences content
Integrate AI/ML/NLP techniques for biomedical ontologies, knowledge graphs, and semantic enrichment
Ensure robust data pipelines, data lakes, and real-time streaming systems are in place for research, commercial, and clinical data
Partner with research scientists, clinical teams, data science, and IT stakeholders to define requirements and deliver impactful search solutions
Collaborate with data governance and compliance teams to ensure search systems adhere to healthcare regulations (HIPAA, GxP, FAIR data principles)
Work closely with product managers and UX teams to ensure intuitive, high-value search experiences
Implement data security best practices across platform layers
Partner with data governance teams to enforce metadata management, lineage tracking, and data access controls

What we offer

Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards

New

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

New

Staff Machine Learning Engineer

We are seeking a highly experienced and strategic Staff Machine Learning Enginee...

Location

India , Bengaluru

Salary:

Not provided

Bazaarvoice

Expiration Date

Until further notice

Requirements

Minimum of 8+ years of experience in Machine Learning Engineering, Applied Machine Learning, or a related field, with a proven track record of building and maintaining production models
Expert proficiency with the AWS ecosystem for MLOps, including a deep understanding of how to architect solutions using key services like Amazon SageMaker, S3, AWS Step Functions, AWS CloudFormation, Amazon CloudWatch, Amazon Managed Streaming for Apache Kafka (MSK), and Amazon Bedrock
Deep expertise in building and deploying scalable solutions for NLP, including experience with challenges such as sarcasm detection, polysemy, and managing multilingual data
Experience with a variety of ML algorithms and models, including traditional supervised and unsupervised learning, deep learning, and modern Generative AI techniques (e.g., LLMs, RAG, Prompt Engineering)
Proficiency with ML frameworks and libraries such as PyTorch, TensorFlow, and scikit-learn, with an ability to adapt and tune open-source or pre-trained models
A strong understanding of core software engineering principles, including design patterns, data structures, testing, security, and version control
Experience with continuous integration (CI/CD) and regression testing
The ability to translate complex business problems into viable technical solutions and communicate findings to stakeholders in non-technical terms

Job Responsibility

Lead the design, development, and deployment of complex, production-grade ML systems and data pipelines, particularly for Natural Language Processing (NLP) and Generative AI applications
Serve as a domain expert in the application of AI to solve core business challenges, including sentiment analysis, content moderation, product recommendations, and personalized search
Drive innovation by identifying and addressing high-impact technical challenges and long-standing technical debt within our ML and data infrastructure
Provide technical mentorship to other engineers on the team and beyond, raising the bar for engineering excellence, maintainability, and best practices across the organization
Collaborate closely with Data Scientists, Product Managers, and other engineering teams to translate complex business requirements into robust, data-driven ML solutions
Implement and oversee MLOps practices, including automated CI/CD pipelines, model monitoring, and governance, to ensure our systems are reliable, reproducible, and performant at scale
Implement robust observability frameworks to proactively detect and diagnose issues like model drift, data quality anomalies, and performance degradation in production

New

Staff Backend Engineer - ID Graph

We are looking for a Staff Backend Engineer to join our Identity Graph team and ...

Location

United States

Salary:

190000.00 - 210000.00 USD / Year

Socure

Expiration Date

Until further notice

Requirements

8+ years of backend software engineering experience
1+ years in a staff/principal-level role
Expertise in search technologies like ElasticSearch or Vespa, including deployment, tuning, and query optimization
Strong cloud-native experience, especially with AWS services like S3, SQS, Lambda, and Kafka
Proven ability to design, build, and maintain distributed systems handling high-volume data streams and real-time requirements
Deep knowledge of Kubernetes-based application development and deployment
Strong proficiency in one or more backend programming languages (Java, Scala, Go, Python, etc.)
Experience benchmarking and deploying machine learning models (ranking, reranking, classification) into production search pipelines
Strong problem-solving, communication, and collaboration skills
Familiarity with SQL/NoSQL and Graph databases

Job Responsibility

Lead architecture and development of high-performance, cloud-native Entity Resolution APIs
Design and implement batch and streaming data pipelines using tools like Kafka, SQS, and Spark to build and update the underlying search index
Build and maintain low-latency search APIs powered by ElasticSearch or Vespa to support real-time entity linking
Collaborate with data scientists to integrate and deploy ranking models to improve search result quality
Own the end-to-end lifecycle of applications deployed on Kubernetes, from development and CI/CD to monitoring and scaling
Conduct performance tuning and debugging of search systems under high throughput and low-latency requirements
Develop tools and metrics to benchmark search quality and system performance
Partner with cross-functional teams in data science, infrastructure, and product to deliver reliable, scalable solutions
Lead design discussions and planning for backend services that incorporate model inference, SQL/NoSQL and Graph databases

What we offer

Equity
Comprehensive benefits
Annual discretionary performance bonus or commissions plans

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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