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Perplexity

Perplexity

www.perplexity.ai

4 Jobs

1,338 Employees

About the Company

The most powerful answer engine. Powering curiosity with answers backed by up-to-date sources. This is where knowledge begins.

Listed Jobs

Company background Company brand
Company Name
Perplexity
Job Title
AI Researcher
Job Description
**Job Title**: AI Researcher **Role Summary** Conduct cutting‑edge research and development on large‑scale language models (LLMs) for AI‑powered search and agent products. Lead the design, training, and deployment of post‑training techniques such as SFT, DPO, and GRPO, and integrate advanced models into production systems. Collaborate closely with engineering and product teams to translate user needs into model performance improvements. **Expectations** - Deliver high‑impact research that advances state‑of‑the‑art LLM capabilities for search and agent experiences. - Own the end‑to‑end pipeline from data ingestion to model evaluation and production rollout. - Demonstrate ownership and initiative, taking full responsibility for research projects from conception to deployment. **Key Responsibilities** - Post‑train SOTA LLMs using supervised and reinforcement learning methods (SFT, DPO, GRPO). - Scale model performance leveraging large query/answer datasets across multiple product lines. - Research and implement personalization and preference optimization to enhance user experience. - Innovate internal improvements to training pipelines, infrastructure, and model performance. - Convert research ideas into deployable algorithms and conduct rigorous experimentation. - Build and maintain robust training frameworks (e.g., Megatron/PyTorch) for large‑scale model training. - Integrate trained models into the product ecosystem ensuring seamless operation. - Collaborate with cross‑functional teams (engineering, product, data science) to maintain cohesive AI experiences. **Required Skills** - 2–6 years of experience with large‑scale LLM development and deep learning systems. - Proficiency in Python and PyTorch; additional familiarity with other ML frameworks is a plus. - Hands‑on experience with post‑training techniques and reinforcement learning for language models. - Strong programming and problem‑solving skills, with a self‑starter mindset. - Excellent communication and teamwork abilities. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field (master’s preferred). - PhD is a strong advantage but not mandatory. ---
San francisco, United states
Hybrid
13-11-2025
Company background Company brand
Company Name
Perplexity
Job Title
AI Engineer, Applied ML
Job Description
Job Title: AI Engineer, Applied ML Role Summary: Design, build, and iterate AI models for user personalization, query understanding, and content discovery. Own the full model lifecycle, from research through production deployment, ensuring measurable impact on product metrics. Expactations: Deliver scalable, production‑ready ML/AI solutions that drive user engagement. Evaluate models rigorously, conduct A/B tests, and iterate improvements. Collaborate effectively with engineering, product, design, and data science teams in a fast‑paced environment. Stay updated with state‑of‑the‑art research and incorporate new techniques into product iterations. Key Responsibilities: - Apply advanced ML and large‑language model (LLM) techniques to personalize content, model user intent, and surface relevant feeds. - Conduct offline and online experimentation, define metrics, and analyze results to assess model quality and impact. - Own the end‑to‑end model lifecycle: data analysis, feature engineering, training, evaluation, deployment, and monitoring. - Collaborate cross‑functionally to align AI capabilities with product goals and user needs. - Continuously evaluate and integrate emerging research, algorithms, and best practices into the development pipeline. Required Skills: - 5+ years in building and shipping large‑scale ML/AI models for user‑facing products. - Deep expertise in deep learning frameworks (PyTorch, TensorFlow, JAX), LLMs, retrieval systems, summarization, recommendation, NLP, and ranking. - Strong Python programming, production‑ready codemanship, and collaborative Git workflow. - End‑to‑end ML lifecycle experience: data analysis, feature engineering, iterative model development, rigorous evaluation, and monitoring. - Excellent communication, teamwork, and cross‑functional collaboration in agile settings. - Curiosity and focus on user/product impact; passion for advancing applied ML/AI. Required Education & Certifications: - Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, or a related technical field (or equivalent professional experience).
San francisco, United states
Hybrid
Mid level
13-11-2025
Company background Company brand
Company Name
Perplexity
Job Title
Backend Software Engineer - Mobile
Job Description
**Job Title** Backend Software Engineer – Mobile **Role Summary** Design, implement, and scale the backend systems that power our web, mobile, and browser products, with a focus on high‑volume data ingestion, processing, and delivery. **Expectations** - Deliver robust, low‑latency services that meet evolving product requirements. - Collaborate closely with product managers, frontend engineers, and cross‑functional AI/Search/Data Science teams. - Drive continuous optimization of architecture, performance, and cost for AWS‑based infrastructure. **Key Responsibilities** 1. Build scalable pipelines for ingesting data from web, files, and external sources. 2. Optimize database (PostgreSQL, DynamoDB) and cache (Redis) interactions for throughput and reliability. 3. Manage a complex orchestration system, coordinating multiple services and interfaces. 4. Load‑balance and scale services to accommodate rapidly changing traffic patterns. 5. Partner with AI/LLM teams to iterate on non‑deterministic data processing systems. **Required Skills** - Strong Python programming experience. - Deep knowledge of relational (PostgreSQL) and NoSQL (DynamoDB) databases, plus cache technologies. - Proven experience building and operating AWS cloud infrastructure at scale. - Familiarity with high‑scale, non‑deterministic systems such as large‑language models. - Performance tuning, load‑balancing, and system‑level debugging. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent professional experience). - Minimum 4 years of production software engineering experience. - AWS certification (Solutions Architect, DevOps, or similar) is a plus.
San francisco, United states
Hybrid
Junior
13-11-2025
Company background Company brand
Company Name
Perplexity
Job Title
AI Inference Engineer (London)
Job Description
**Job Title:** AI Inference Engineer **Role Summary:** Design, develop, and maintain high‑performance APIs for deploying large‑scale machine‑learning models in production environments. Optimize inference pipelines for latency, throughput, and resource efficiency while ensuring reliability, observability, and rapid response to system incidents. **Expectations:** - Deliver robust, scalable inference solutions for internal and external users. - Continuously benchmark and eliminate performance bottlenecks. - Maintain high availability and quick incident resolution. - Apply research insights to improve LLM inference performance. **Key Responsibilities:** - Build and expose inference APIs using Python, Rust, and C++. - Integrate deep‑learning frameworks (PyTorch, TensorFlow, ONNX) with inference engines (Triton). - Optimize GPU usage via CUDA kernels and batch strategies (continuous batching, quantization, etc.). - Monitor system health, improve observability dashboards, and troubleshoot outages. - Investigate and implement novel LLM inference optimizations. - Collaborate with cross‑functional teams to define deployment workflows on Kubernetes. **Required Skills:** - Proficiency in Python, Rust, and C++ programming. - Hands‑on experience with PyTorch, TensorFlow, ONNX, and Triton inference servers. - Familiarity with LLM architectures and common optimization techniques (continuous batching, quantization, pruning). - Strong knowledge of GPU architecture, CUDA programming, and kernel optimization. - Experience deploying services on Kubernetes (containers, scaling, rollout). - Ability to benchmark performance, analyze bottlenecks, and implement improvements. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience). - No mandatory certifications; relevant industry certifications (e.g., NVIDIA CUDA, Kubernetes Administrator) are a plus.
London, United kingdom
On site
17-11-2025