Software Engineering Intern (2027 Start) - Belgrade

Perplexity is looking for a Backend/Infrastructure Engineer Intern to support our small, high-impact team building the systems that power our search experience. You will work closely with experienced engineers to help design, build, and operate robust infrastructure and backend services that keep Perplexity fast, reliable, and scalable. Internship program: 12 - 24 weeks, full-time, part-time, in-person in the Belgrade office. Responsibilities: Build and maintain infrastructure that supports high-performance search systems, with mentorship from senior engineers. Design internal tools and automation to improve developer workflows and operational efficiency. Support the design, deployment, and monitoring of cloud-native systems on AWS. Contribute to improving CI/CD pipelines, testing infrastructure, and release processes. Debug and optimize Linux-based services, containers, and backend systems. Contribute to product codebases, primarily using Rust, Go or C++. Qualifications: Working towards a degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Familiarity with at least one programming language such as Go, Rust, or C/C++, through coursework or projects. Basic understanding or exposure to cloud infrastructure (e.g. AWS) and Linux systems is a plus, not a requirement. Interest in infrastructure, distributed systems, or backend engineering, with willingness to learn about CI/CD, monitoring, and performance. A proactive and curious learner who enjoys collaborating in a fast-paced, innovative environment What we're looking for: You’ve built something you’re proud of: Not just a class assignment - we want to see a project you genuinely cared about and took the initiative to build and finish. You’re currently enrolled at a Serbian university: Bachelor’s, Master’s, or PhD program or you’re self-taught with a strong passion for software engineering and technology. You’re curious, persistent, and self-driven: you take ownership, work t

Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, part-time, in-person in the Belgrade office. Responsibilities: Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. Support deployment and monitoring of search and ranking models in a scalable and performant way. Help build and iterate on RAG pipelines for grounding and answer generation. Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment Experience with Rust will be a plus What we're looking for: You’ve built something you’re proud of: Not just a class assignment - we want to see a project y

Perplexity is looking for an Infrastructure Engineer to own and improve the backend systems behind our latency-sensitive search stack. You’ll work across high-QPS Rust and Go services, distributed retrieval systems, cloud infrastructure, observability, and deployment tooling. This role combines infrastructure expertise with software engineering. You’ll take systems from design through production operation and use AI-native tools where they meaningfully improve engineering and operational workflows Responsibilities Build and operate scalable, low-latency infrastructure for search serving and retrieval. Design and improve distributed backend systems that handle high request volumes. Debug and optimize Linux systems, containers, networking, and production services. Improve reliability through observability, capacity planning, performance profiling, and incident response. Design, deploy, and operate cloud-native systems, primarily on AWS and Kubernetes. Build internal tools and automation for development, testing, debugging, and infrastructure operations. Improve CI/CD pipelines, release processes, and production rollout safety. Contribute directly to product codebases across Rust, Go, and other systems languages. Own systems end to end, from architecture and implementation to deployment and production operation. Requirements Strong experience with cloud infrastructure, distributed systems, and automation. Deep understanding of Linux internals, performance analysis, and production debugging. Experience building or operating latency-sensitive, high-throughput backend systems. Experience with containers, orchestration, observability, and infrastructure as code. Experience building or maintaining CI/CD systems and release tooling. Fluency in at least one systems language, such as Rust, Go, C++, or Java. Comfort working across infrastructure and application-level code. Strong ownership and the ability to operate effectively in a fast-moving environment. Nice To Have Experie

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

Perplexity is seeking an experienced Machine Learning Engineer to improve search quality across the middle and later stages of ranking. We are looking for a strong ranking generalist who can own ambiguous problems end to end and brings exceptional depth in either neural ranking or production ranking systems. Responsibilities Push search quality forward through models, data, evaluation, infrastructure, or any other leverage available. Own ranking-quality problems end to end: define the evaluation, identify the bottleneck, build the solution, and ship it safely. Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate. Build and operate ranking infrastructure, including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring. Make sound trade-offs across quality, latency, reliability, cost, and engineering complexity. Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome. Qualifications Deep understanding of search or recommender systems and their evaluation. Proven ownership of a large-scale production ranking system or a substantial class of quality problems. Strong machine learning and software engineering skills across data, models, serving, and monitoring. Ability to drive ambiguous, cross-team problems without continuous task decomposition. Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime.

P-1414 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, Databricks has started a multi-year journey to build the best Data Intelligence Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. From the Storage Engine (data layout, encryption, caching, ...) to the Query Engine (Vectorization, Query Optimization, …), we want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads. As a software engineer, you will join as a founding member of the not only the Belgrade site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values (own-it, data decide, teamwork, customer-obsessed). The responsibilities you will have : Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: BS in Computer Science or equivalent practical experience in databases or distributed systems Comfortable working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 3+ years of production level experience in either Java, Scala or C++ Solid foundation in algorithms and data structures and their real-world use cases Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop) About Databricks Databricks is the Data and A