deepset

Role Description As a Solution Engineer at deepset, you will apply cutting-edge NLP techniques to real-world enterprise problems. You will develop deep expertise across the full spectrum of NLP methods within Haystack including: - Dense retrieval - Question Answering - Generative QA - Summarization - RAG pipelines You will collaborate closely with our open-source and product teams to shape the best solutions for each engagement. This role sits at the intersection of professional services consultant, senior AI/NLP engineer, and trusted technical advisor. Exemplary engagement: You will partner with data scientists from a leading aerospace corporation to enhance search functionality across pilot manuals. This means: - Understanding their data and domain - Evaluating methods (DPR, QA, TableQA) against their requirements - Designing annotation workflows for expert labellers - Continuously analysing incoming labels - Training and iterating models - Driving step-by-step performance improvements until production targets are met Qualifications - Fluency in German (C1/C2 or native) and strong professional English - 5+ years of industry experience applying data science or NLP methods to real-world data - University degree in Computer Science or a comparable qualification - Proficiency in Python and strong working knowledge of ML/DL/NLP methods and recent model architectures (Transformers, LLMs, retrieval models) - Hands-on experience with Haystack, Hugging Face Transformers, PEFT, or comparable NLP frameworks - Experience managing customer-facing projects: defining scope, setting timelines, communicating results - Excellent communication skills with both technical (data scientist, ML engineer) and non-technical (business, C-suite) stakeholders - An intense desire to learn and a track record of rapidly acquiring new skills Requirements - Data science consulting experience and/or hands-on experience with data annotation workflows (nice to have) - Experience with deepset Cloud or other enterprise NLP/search platforms (nice to have) - Familiarity with dense retrieval (DPR), Question Answering, generative QA, TableQA, and Summarization methods (nice to have) - Understanding of RAG architectures and vector databases (e.g. Weaviate, Pinecone, OpenSearch) (nice to have) - Experience with model fine-tuning via PEFT (LoRA, QLoRA) and large-scale data curation (nice to have) - Contributions to open-source NLP libraries or a public technical profile (blog, talks, GitHub) (nice to have) - Aspiration to grow into a senior expert or team lead position as the Solutions team scales (nice to have) Benefits - Competitive salary + equity (ESOP). We benchmark against above European AI companies. - Remote-first culture with optional access to Munich and Berlin offices. Flexible working hours. - Work on the frontier of enterprise AI. Your solutions will go into production at household-name companies. - Learning budget, conference attendance, access to the best minds in open-source NLP and LLMs. - Transparent, low-ego team. English as the working language, diverse and international colleagues. - 30 days PTO, company offsites, home office setup budget, and more.

TL;DR We're rethinking demand generation as a self-learning system, not just a set of campaigns. This hybrid role sits at the intersection of growth marketing and GTM engineering. You'll own the full enterprise pipeline funnel, building the data and AI-powered demand engine that makes it run and achieve its goals. Why deepset At deepset, we’re making sovereign AI accessible to every organization. With Haystack, thousands of developers build advanced AI applications, while our enterprise platform helps teams scale across use cases, users, and environments. We’re remote-first, flexible, and built on trust and ownership. You’ll work alongside strong technical talent, take on meaningful challenges, and help turn complex AI into solutions that are practical, reliable, and ready for the real world. What you will do - Full-funnel growth ownership. Own pipeline from awareness to opportunity—across inbound and outbound—connecting Salesforce, HubSpot, LinkedIn, and other tools to power personalized journeys from prospect to customer, with clear attribution to revenue. - Systems builder. You build AI-assisted workflows for campaign creation, messaging, and segmentation including showcasing AI agents powering real GTM workflows on deepset's own platform - High-tempo experimentation & high visibility. You methodically test messaging, audiences, and channels fast across web, paid, email, social, content, and events, scaling what works into playbooks and cutting what doesn't - Cross-functional integrator. Tight feedback loops with Leadership, Sales, Product, DevRel, and RevOps; activating ICPs across developer and enterprise journeys, and implementing refinements and learnings to hit pipeline goals. Requirements - 3+ years in data-driven, AI B2B , deep tech, or developer tools marketing - Proven track record running full-funnel demand with measurable pipeline impact - Comfortable with APIs, automation tools, and data workflows (Python, Claude, Haystack) - You think in hypotheses and have the analytics chops to iterate and prove value - Deep understanding of what resonates with technical audiences and business buyers - Your tools stack: Clay, Salesforce, HubSpot, Google Analytics, LinkedIn Campaign Manager, Webflow, Salesforce, intent analytics (Reo.dev, community analytics) - Deep familiarity with ICP mapping, value-based messaging, audience targeting, and campaign optimization Nice to have - German language skills - Open-source community experience - LLM / AI product marketing background - Early-stage or high-growth startup experience Benefits - Remote-first setup with flexible hours & tech of your choice - 30 days vacation + extra days for family sick leave - Competitive salary & stock options for every team member - Monthly sports & mental health support allowance with Oliva - Annual learning & development budget - Monthly team socials & in-person meetups - Dog-friendly Berlin HQ

TL;DR We're rethinking demand generation as a self-learning system, not just a set of campaigns. This hybrid role sits at the intersection of growth marketing and GTM engineering. You'll own the full enterprise pipeline funnel, building the data and AI-powered demand engine that makes it run and achieve its goals. Why deepset At deepset, we’re making sovereign AI accessible to every organization. With Haystack, thousands of developers build advanced AI applications, while our enterprise platform helps teams scale across use cases, users, and environments. We’re remote-first, flexible, and built on trust and ownership. You’ll work alongside strong technical talent, take on meaningful challenges, and help turn complex AI into solutions that are practical, reliable, and ready for the real world. What you will do - Full-funnel growth ownership. Own pipeline from awareness to opportunity—across inbound and outbound—connecting Salesforce, HubSpot, LinkedIn, and other tools to power personalized journeys from prospect to customer, with clear attribution to revenue. - Systems builder. You build AI-assisted workflows for campaign creation, messaging, and segmentation including showcasing AI agents powering real GTM workflows on deepset's own platform - High-tempo experimentation & high visibility. You methodically test messaging, audiences, and channels fast across web, paid, email, social, content, and events, scaling what works into playbooks and cutting what doesn't - Cross-functional integrator. Tight feedback loops with Leadership, Sales, Product, DevRel, and RevOps; activating ICPs across developer and enterprise journeys, and implementing refinements and learnings to hit pipeline goals. Requirements - 3+ years in data-driven, AI B2B , deep tech, or developer tools marketing - Proven track record running full-funnel demand with measurable pipeline impact - Comfortable with APIs, automation tools, and data workflows (Python, Claude, Haystack) - You think in hypotheses and have the analytics chops to iterate and prove value - Deep understanding of what resonates with technical audiences and business buyers - Your tools stack: Clay, Salesforce, HubSpot, Google Analytics, LinkedIn Campaign Manager, Webflow, Salesforce, intent analytics (Reo.dev, community analytics) - Deep familiarity with ICP mapping, value-based messaging, audience targeting, and campaign optimization Nice to have - German language skills - Open-source community experience - LLM / AI product marketing background - Early-stage or high-growth startup experience Benefits - Remote-first setup with flexible hours & tech of your choice - 30 days vacation + extra days for family sick leave - Competitive salary & stock options for every team member - Monthly sports & mental health support allowance with Oliva - Annual learning & development budget - Monthly team socials & in-person meetups - Dog-friendly Berlin HQ

TL;DR We're hiring a Site Reliability Engineer to own and evolve deepset's cloud and customer infrastructure end to end. You'll work across SaaS, private cloud, and on-prem environments to make our self-hosted platform production-ready, drive CI/CD and GitOps maturity, and reduce complexity at scale. Your work will directly shape how deepset's AI platform is built, deployed, and scaled for our own cloud and for customers running it in their own environments. Why deepset At deepset, we’re on a mission to make custom AI solutions accessible to every organization. With Haystack, thousands of developers build advanced LLM applications every day, while our enterprise-ready AI Platform helps companies turn large language models into business value. We’re remote-first, flexible, and built on a culture of trust and ownership. You’ll collaborate with top-tier tech talent, tackle meaningful challenges, and help transform complex AI into solutions that are simple, powerful, and ready for the real world. What you will do You won’t just “keep things running” - you’ll help define how our platform is built, deployed, and scaled across cloud and customer environments. - Build and operate real-world infrastructureDesign, configure, and evolve infrastructure that runs both in our cloud and inside customer environments (SaaS, private cloud, on-prem). - Make self-hosted production-readyHelp us deliver a production-grade, self-hosted platform that can be deployed on any Kubernetes setup in weeks - not months. - Drive automation & platform maturityImprove CI/CD pipelines, GitHub workflows, and GitOps setups so teams can ship faster with confidence. - Reduce complexity and costContinuously simplify systems and optimize infrastructure spend without compromising performance or reliability. - Shape how we buildChampion best practices in reliability, scalability, and security across the organization, not as rules, but as working systems. Requirements - 2-5 years of experience working with large-scale production infrastructure - Fluent German language skills - Experience with distributed or service-oriented architectures - Hands-on expertise with: - AWS - Kubernetes - CI/CD and GitOps (e.g. ArgoCD) - Working knowledge of Infrastructure as Code (Terraform preferred) - Solid troubleshooting skills - you can debug across systems, not just within one layer - A pragmatic mindset: you balance speed, simplicity, and reliability - Ownership and accountability - you take responsibility for systems end-to-end - Ability to work independently while staying aligned with the team’s goals Nice to have - Familiarity with observability stacks (e.g. Datadog, Prometheus) - Experience optimizing cloud costs at scale - Interest or experience in Machine Learning / LLM systems - Experience improving developer experience and platform tooling using AI agents - Contributions to SRE practices like postmortems, SLIs/SLOs, and reliability engineering culture Benefits - Remote-first setup with flexible hours & tech of your choice - 30 days vacation + extra days for family sick leave - Competitive salary & stock options for every team member - Monthly sports & mental health support allowance with Oliva - Annual learning & development budget - Monthly team socials & in-person meetups - Dog-friendly Berlin HQ

TL;DR We're hiring a Site Reliability Engineer to own and evolve deepset's cloud and customer infrastructure end to end. You'll work across SaaS, private cloud, and on-prem environments to make our self-hosted platform production-ready, drive CI/CD and GitOps maturity, and reduce complexity at scale. Your work will directly shape how deepset's AI platform is built, deployed, and scaled for our own cloud and for customers running it in their own environments. Why deepset At deepset, we’re on a mission to make custom AI solutions accessible to every organization. With Haystack, thousands of developers build advanced LLM applications every day, while our enterprise-ready AI Platform helps companies turn large language models into business value. We’re remote-first, flexible, and built on a culture of trust and ownership. You’ll collaborate with top-tier tech talent, tackle meaningful challenges, and help transform complex AI into solutions that are simple, powerful, and ready for the real world. What you will do You won’t just “keep things running” - you’ll help define how our platform is built, deployed, and scaled across cloud and customer environments. - Build and operate real-world infrastructureDesign, configure, and evolve infrastructure that runs both in our cloud and inside customer environments (SaaS, private cloud, on-prem). - Make self-hosted production-readyHelp us deliver a production-grade, self-hosted platform that can be deployed on any Kubernetes setup in weeks - not months. - Drive automation & platform maturityImprove CI/CD pipelines, GitHub workflows, and GitOps setups so teams can ship faster with confidence. - Reduce complexity and costContinuously simplify systems and optimize infrastructure spend without compromising performance or reliability. - Shape how we buildChampion best practices in reliability, scalability, and security across the organization, not as rules, but as working systems. Requirements - 2-5 years of experience working with large-scale production infrastructure - Fluent German language skills - Experience with distributed or service-oriented architectures - Hands-on expertise with: - AWS - Kubernetes - CI/CD and GitOps (e.g. ArgoCD) - Working knowledge of Infrastructure as Code (Terraform preferred) - Solid troubleshooting skills - you can debug across systems, not just within one layer - A pragmatic mindset: you balance speed, simplicity, and reliability - Ownership and accountability - you take responsibility for systems end-to-end - Ability to work independently while staying aligned with the team’s goals Nice to have - Familiarity with observability stacks (e.g. Datadog, Prometheus) - Experience optimizing cloud costs at scale - Interest or experience in Machine Learning / LLM systems - Experience improving developer experience and platform tooling using AI agents - Contributions to SRE practices like postmortems, SLIs/SLOs, and reliability engineering culture Benefits - Remote-first setup with flexible hours & tech of your choice - 30 days vacation + extra days for family sick leave - Competitive salary & stock options for every team member - Monthly sports & mental health support allowance with Oliva - Annual learning & development budget - Monthly team socials & in-person meetups - Dog-friendly Berlin HQ