Forward Deployed Engineer (m/f/d) at praxipal | Berlin

Join Our Innovative TeamAt Prior Labs, we are pioneering the development of foundation models that adeptly comprehend tabular data, which serves as the cornerstone of both scientific and business endeavors. While foundation models have revolutionized the fields of text and image processing, structured data has largely been overlooked. We are seizing the opportunity to address this $600 billion market and fundamentally transform how organizations manage scientific, medical, financial, and business data.Our Achievements: We stand at the forefront of structured data machine learning. Our TabPFN v2 model, featured in Nature, has set a new benchmark in tabular machine learning. Since its launch, we have enhanced our model capabilities over 20 times, achieved over 2.5 million downloads, garnered more than 5,500 stars on GitHub, and are witnessing rapid adoption across both research and industry sectors. We are currently developing the next generation of tabular foundation models and actively commercializing them in collaboration with global enterprises in Europe and the U.S.About Our Team: We are a compact, highly selective team of over 20 engineers and researchers, chosen from more than 5,000 applicants. Our team includes talents from industry giants like Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. We are led by the creators of TabPFN and supported by renowned AI researchers, including Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet our exceptional team here.Looking Ahead: With backing from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are experiencing rapid growth. This is an exciting opportunity to join us and contribute to shaping the future of structured data AI. Read our manifesto.Your ImpactIn this role, you will do more than simply deploy models; you will play a crucial role in delivering transformative solutions that redefine how organizations leverage data. You will work at the intersection of advanced AI technology and practical applications, collaborating closely with our key strategic partners.

Join Us as a Forward Deployed Engineer Intern in Berlin - m/f/d - Full-TimeAt Plato, we are on a mission to revolutionize the global trade economy by establishing the digital backbone for the wholesale distribution sector, valued at $53 trillion. Our platform empowers modern wholesalers by centralizing their operations and data into a unified analytics and workflow hub, utilizing advanced data science and AI to automate processes and mitigate labor shortages, enabling small to medium-sized businesses to compete effectively with larger corporations.Why We Do What We DoWe believe that the future of wholesale is profoundly data-driven. Industrial SMEs are eager to adopt proactive strategies but often lack the necessary technology. Our founders, hailing from a wholesale background, have assembled a stellar team with experience from Big Tech, venture capital, and leading consulting firms, aiming to transform this $48 trillion industry. Our premier product harnesses cutting-edge data science to deliver personalized demand forecasts and product recommendations, paired with intelligent workflow automation.About the RoleAs a Forward Deployed Engineer Intern, you will serve as the vital link between business and technology, overseeing the technical deployment of our AI platform for new clients. From ERP integrations to enabling AI features, your role is crucial in ensuring that Plato provides tangible value from the outset.Your MissionOwn deployments from start to finish, collaborating with Engineering, Customer Success, and clients to launch applications swiftly and efficiently.Translate complex integration and customer requirements into clear, actionable technical directives for our engineering team.Innovate AI-driven features based on client feedback, from document automation to in-app intelligence enhancements.

Join Taktile as a Lead Forward Deployed Engineer, where you will play a pivotal role in bridging cutting-edge technology with client needs. Your expertise will guide the deployment of innovative solutions, ensuring seamless integration and optimization of our products.

As a Senior Forward Deployed Engineer at Taktile, you will play a pivotal role in our mission to empower businesses through data-driven decision-making. You will work closely with our clients, leveraging your technical expertise to implement innovative solutions that drive efficiency and growth. Your responsibilities will include designing and deploying complex systems, collaborating with cross-functional teams, and providing ongoing support to ensure our clients achieve their goals.

Veo stands as a global pioneer in AI-driven sports camera technology. Our cutting-edge, fully automated camera solution empowers sports teams to capture matches and training sessions without the need for a camera operator. We are passionate about democratizing the world of sports by enabling video analysis for teams at every level—a luxury that was once reserved for a select few. Each week, over 40,000 clubs across more than 90 countries utilize our technology to record their games.What truly distinguishes us is our people. We are a diverse assembly of innovative thinkers, creators, and problem-solvers, dedicated to delivering an exceptional product—while enjoying the process.The OpportunityAs a Forward Deployed Engineer at Veo, you will engage at the nexus of engineering and external partnerships, transforming integration needs into scalable working solutions. This position is integral to Veo’s API team and fuses hands-on engineering with close collaboration among teams and partners.You will report to the Engineering Manager and be based in our Berlin office, collaborating as part of a small, focused team alongside engineers and a Technical Product Manager. In addition to working on Veo’s API—a core feature—you will interact directly with partners to grasp their technical requirements. You will help shape integration strategies and deliver solutions that prioritize speed, quality, and maintainability.This role is ideal for someone who thrives on problem-solving, feels comfortable transitioning between discussions and coding, and is driven by the desire to make practical solutions work effectively.

Join Aircall, a leading AI-driven customer communications platform that empowers over 22,000 businesses globally to enhance revenue, expedite issue resolution, and scale customer-facing teams effectively. We are revolutionizing customer interactions by integrating voice, SMS, WhatsApp, and AI into a unified workspace.Our driving force is simple: enable teams to work smarter, not harder. Our AI Voice Agent automates routine calls, AI Assist simplifies post-call tasks, and AI Assist Pro provides real-time guidance, allowing teams to excel. This results in increased revenue, quicker resolutions, and scalable teams that operate with confidence.Headquartered in Paris, with a robust North American presence in Seattle and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City, we offer a product cherished by customers and a rapidly growing business supported by top-tier investors and driven by swift AI advancements.At Aircall, you will become part of a dynamic organization. We are ambitious, product-focused, and execution-oriented, prioritizing visible impact, swift decision-making, and genuine growth.Our Work Culture: We are customer-centric, data-informed, and committed to achieving significant results. We emphasize ownership, ongoing learning, and thoughtful speed. If you thrive in a collaborative, fast-paced environment where trust and impact are paramount, you will feel at home with us.Team OverviewThe Forward Deployed Engineering team at Aircall bridges our cutting-edge AI Agents technology with real-world SMB workflows. We transform potential into production, delivering automation that enhances customer experiences, increases productivity, and unlocks new business opportunities. This role is hands-on and dynamic, situated at the intersection of technical consulting, project leadership, and AI adoption strategy. While you don't need to be a full-time software engineer, fluency in APIs, strong project management skills, and a desire for continuous learning and model development are essential.

At Synthflow AI, we are revolutionizing the way businesses handle communication through our no-code platform for voice AI agents. Our solutions automate phone calls across contact center operations and business process outsourcing (BPO) at scale, enabling mid-market and enterprise companies to efficiently manage routine calls, ultimately saving time and resources.Our impact is already significant:More than 5 million hours of contact center operations saved.35% increase in calls answered compared to traditional operators.Handled 45 million calls with an impressive 99.9% uptime.Supported by industry leaders such as Accel, Atlantic Labs, and Singular, and trusted by over 1,000 customers, Synthflow is at the forefront of the conversational AI movement.Role OverviewAs a Forward Deployed Engineer (FDE) at Synthflow, you will play a pivotal role in bridging our advanced technology with our clients' operational success. You will collaborate closely with enterprise clients post-sale to implement, customize, and optimize our AI phone agent solutions tailored to their specific environments.This role demands a unique blend of technical expertise and customer-centric empathy, as you will translate complex business challenges into scalable and effective solutions. You will ensure seamless deployment, user adoption, and measurable impact, making you both a builder and a strategic partner in our clients' journeys toward maximizing the value of Synthflow’s platform.

YOUR MISSION: As a Forward Deployed Engineer in DevOps, your mission is to develop and enhance the specialized infrastructure that supports our custom agent integrations for our key clients. You will serve as a pivotal technical resource for our team, enabling our customer-facing Forward Deployed Engineers to swiftly build, deploy, and manage tailored client solutions. By establishing a solid, automated, and self-service platform, you will facilitate the efficient delivery of high-quality, reliable custom services. IN THIS ROLE YOU WILL: Design, build, and oversee cloud infrastructure dedicated to hosting custom services created by the Agent Integration Engineering team. Create adaptable and reusable CI/CD pipeline templates that the integration team can easily implement to automate their service deployments. Promote Infrastructure as Code to develop standardized yet customizable service environments, ensuring rapid provisioning and consistency for new integrations. Manage a Kubernetes-based environment crafted for hosting a variety of integration services, with a focus on security, isolation, and resource allocation. Deploy comprehensive monitoring and observability solutions, granting the integration team deep insights into the performance and health of their specific services. Act as the primary DevOps partner for the Forward Deployed Engineering team, understanding their processes, anticipating their needs, and eliminating infrastructure-related barriers. Develop automation scripts using Python, Go, or Bash to optimize the lifecycle of custom integration services from creation to retirement. Support and modernize legacy Azure infrastructure, assisting in the transition of workloads to a standardized Kubernetes-based platform in alignment with Parloa’s engineering practices.

At praxipal, we are on a mission to revolutionize healthcare administration through AI. Our innovative platform addresses the critical shortage of medical personnel by empowering medical assistants to focus on patient care rather than administrative tasks.Meet Luna, our AI receptionist that has transformed patient communication for over 100 medical practices by automating phone calls and streamlining workflows. As we expand Luna's capabilities to encompass complete patient communication across multiple channels, we aim to automate all administrative processes in medical settings, seamlessly integrating with existing systems.Supported by prominent investors, we are among the fastest-growing healthtech startups in Germany. Our diverse team brings experience from industry leaders such as Palantir, Amazon, and SAP, as well as top academic institutions like the University of Cambridge.We are seeking a dedicated Working Student for the role of Forward Deployed Engineer to take technical ownership of key customer deployments.

Join Almedia, a dynamic and innovative company where ambition meets opportunity. As we strive to become Germany’s next bootstrapped unicorn, we are proud to be recognized as Europe’s third fastest-growing company in 2025 according to the FT1000.At Almedia, we are revolutionizing the marketing landscape by enabling our vast community of over 60 million users to earn rewards for interacting with our advertisers' products, providing a unique approach to user acquisition for major global brands.Machine Learning EngineerIn this pivotal role, you will be responsible for the design, development, and scaling of production-grade machine learning solutions that drive the innovation of Almedia’s offerings and support our growth trajectory.This is a hands-on position where you will actively engage in coding, development, and deployment of solutions.Key Challenges You Will Tackle:Creating and optimizing user reward systems tailored to player behavior and market trends.Spearheading the development of personalized, real-time reward mechanisms.Identifying and addressing underperforming reward initiatives and their underlying issues.Your Responsibilities Include:Overseeing the complete delivery lifecycle: develop, deploy, and optimize scalable solutions and services.Providing technical guidance on ML projects, upholding best practices and ensuring high coding standards.Aligning technical capabilities with business goals to capitalize on high-value opportunities.Utilizing advanced statistical and causal inference techniques to secure robustness and reliability in solutions.Collaborating with product and engineering teams to convert business challenges into predictive, data-driven solutions.Qualifications Required:Demonstrated expertise in building, deploying, and maintaining production-level solutions and services, preferably in adtech or high-scale environments.Solid understanding of statistical analysis (A/B testing, regression, probability).Proficient in programming with Python and SQL, with practical experience in cloud technologies.Proven ability to mentor and guide ML engineers and cross-functional colleagues.Excellent communication skills and a collaborative mindset.

Machine Learning Engineer Company Overview At Orcrist Technologies, we are pioneers in building the Orcrist Intelligence Platform (OIP), a cutting-edge Kubernetes-based data intelligence system. Our platform is offered as either SaaS or a self-hosted/on-premises solution, including air-gapped deployments. We integrate data processing, machine learning, and artificial intelligence within a modern web application to empower mission-critical clients across both public and private sectors. Role Overview As a Machine Learning Engineer, you will spearhead the incubation and validation of new ML initiatives from conception to execution. In this innovative role, you will create adoption-ready prototype vertical slices that encompass data flows, model serving, evaluation, and seamless product integration. You will ensure clear handoff of artifacts to delivery teams so they can effectively productize and maintain them for the long haul. Key Responsibilities Develop ML prototype vertical slices that bridge data ingestion and processing with inference and end-user product outcomes (such as search functionalities, insights generation, and user experience flows). Establish evaluation harnesses and decision-making artifacts including datasets, baselines, and performance metrics (quality, latency, cost), along with actionable go/no-go recommendations. Package prototypes for seamless adoption: containerize services, specify reproducible deployment strategies, and create comprehensive runbooks/checklists. Collaborate with Research and Data Engineering teams for dataset curation, annotation processes, experiment tracking, and iterative improvements. Ensure operational credibility of prototypes through instrumentation, monitoring, and foundational security/compliance practices (including handling of personally identifiable information and provenance considerations). Candidate Profile A minimum of 3 years of experience in ML engineering or MLOps, with a proven track record of delivering tangible systems. Proficient in Python and experienced with PyTorch/Transformers; adept at transforming models from notebooks into deployable services. Hands-on experience with Kubernetes and containerization; capable of deploying and troubleshooting within production-like environments, including offline or air-gapped constraints. A strong evaluation mindset and monitoring discipline; effective in clearly articulating trade-offs. Eligibility to work in Germany; EU or NATO citizenship is preferred, and export-control screening applies. Preferred Qualifications Experience with GPU serving and optimization techniques (e.g., Triton/KServe, ONNX/TensorRT, batching, quantization). Familiarity with streaming and pipeline tools (e.g., Kafka, Ray, Beam/Flink/Spark) and integrations involving search, vector, and graph technologies. Proficiency in the German language (B1+) and/or experience working with regulated or public-sector datasets and workflows. What We Offer A modern ML stack designed to operate within real-world constraints: Kubernetes, streaming technologies, and hybrid/on-prem/air-gapped deployments. A remote-first work environment in Germany, complemented by regular workshops in Berlin, 30 days of vacation, and support for equipment and learning budgets. High impact: your prototypes will pave the path for groundbreaking solutions.

About UsHelsing is a cutting-edge AI company dedicated to advancing defense technologies. Our mission is to safeguard democratic values and ensure that societies can make autonomous decisions while upholding ethical standards. We are committed to responsible technology development and deployment, particularly in the realm of AI.Our team comprises driven engineers, AI experts, and client-facing program managers united by a common purpose: tackling the most challenging and significant problems. We foster a culture of transparency and encourage open discussions surrounding the ethical implications of technology in defense.The PositionAs an AI Research Engineer at Helsing, you will be at the forefront of innovating autonomous decision-making systems for defense. Your work will encompass a wide range of AI applications, including extensive data processing, reinforcement learning agent training, and the development of large-scale foundational models. Collaborating within a diverse team, your responsibilities will include architecting and implementing robust tools and platforms that drive these advancements. You will focus on abstracting complex distributed systems to enhance training efficiency and developer productivity. We seek engineers who can effectively blend machine learning with systems engineering to create scalable solutions.Key Responsibilities:Enhance our integrated deep learning frameworks, built on PyTorch, to make them efficient and user-friendly across various applications.Expand our infrastructure and tooling to facilitate faster and larger-scale distributed training.Devise data strategies to manage extensive datasets effectively.

Join Perplexity as a skilled Machine Learning Research Engineer, where you will play a pivotal role in developing cutting-edge search technologies focusing on retrieval and ranking mechanisms.Key Responsibilities:Proactively enhance search quality through innovative models, data strategies, tools, and other effective means.Design and construct essential components of our advanced search platform and model architecture.Create, train, and fine-tune large-scale deep learning models utilizing frameworks like PyTorch, with an emphasis on distributed training and hardware acceleration for retrieval and ranking.Engage in advanced research on representation learning, including contrastive learning and multilingual, multimodal modeling tailored for search and retrieval applications.Implement and deploy models effectively, ranging from boosting algorithms to large language models, ensuring scalability and performance.Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for accurate grounding and answer generation.Collaborate across Data, AI, Infrastructure, and Product teams to ensure swift and high-quality project delivery.

Join Intercom, the leading AI Customer Service company, dedicated to empowering businesses to deliver exceptional customer experiences.Our AI agent, Fin, stands out as the most sophisticated customer service AI solution available, enabling companies to provide constant, flawless service and revolutionize their customer interactions. Fin seamlessly integrates with our Helpdesk to form the Intercom Customer Service Suite, which offers AI-enhanced support for intricate or high-touch inquiries that necessitate human intervention.Founded in 2011, Intercom is trusted by nearly 30,000 global businesses and is committed to redefining customer service standards. Our core values inspire us to innovate relentlessly, operate with speed and intensity, and consistently provide remarkable value to our clients.We believe Berlin is an ideal city for those who share our passion for speed and innovation. The city boasts a unique combination of deep technical expertise and a vibrant creative culture, making it a hub for top-tier talent eager to collaborate on ambitious projects. With close ties to our R&D centers in Dublin and London, Berlin is where the best minds come together to thrive.As we aim to expand our team by hiring 100 professionals across engineering, AI, data science, product, and design over the next year, this is an exciting opportunity to be among the pioneering R&D talents in the region and leave a lasting mark as we develop the world's leading customer agent.What’s the Opportunity?The Machine Learning team at Intercom is at the forefront of defining new ML features, researching cutting-edge algorithms and technologies, and swiftly delivering prototypes to our customers.We are a highly product-focused team, collaborating closely with Product and Design teams. Our dedicated ML product engineers enable rapid transitions to production, often launching beta versions within weeks of successful offline testing.Our passion for machine learning drives us to explore and productize everything from conventional supervised models to advanced unsupervised clustering algorithms and innovative transformer neural network applications. We rigorously test and assess the real customer impact of every model we deploy.What Will I Be Doing?Identify opportunities where ML can generate value for our customers.Determine the optimal ML framing for product challenges.Collaborate with team members and Product and Design stakeholders.

Join Our Internship Program in Berlin!We are excited to announce a full-time, in-person internship opportunity in our Berlin office, lasting between 12 to 24 weeks.Your ResponsibilitiesDrive the advancement of search quality utilizing various models, data, tools, and innovative techniques.Train and fine-tune large-scale deep learning models using PyTorch, employing distributed training methods (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models.Engage in research on representation learning, exploring contrastive learning, multilingual capabilities, evaluation methodologies, and multimodal modeling for enhanced search and retrieval.Design and refine RAG pipelines for effective grounding and answer generation.QualificationsSolid understanding of search and retrieval systems, including quality evaluation metrics and principles.Demonstrated proficiency with PyTorch, particularly in distributed training and performance optimization for large models.A keen interest in representation learning, covering areas such as contrastive learning, dense and sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization, and robust evaluation methods.A publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR) is a plus.

Join Our Innovative TeamAt Prior Labs, we are revolutionizing the way organizations interact with structured data, the cornerstone of science and business. While foundation models have significantly advanced the fields of text and image processing, structured data has largely been overlooked. We are seizing a $600 billion opportunity to transform how scientific, medical, financial, and business data are utilized.Leading the Charge: We are recognized as the premier organization in structured data machine learning. Our TabPFN v2 model, highlighted in Nature, has set a new benchmark in tabular machine learning. Our capabilities have expanded over 20 times since launch, with over 2.5 million downloads and 5,500+ stars on GitHub, leading to rapid adoption in both research and industry. We are now advancing the next generation of tabular foundation models and partnering with major enterprises across Europe and the US.Our Team: We are a tight-knit team of over 20 engineers and researchers, handpicked from a pool of more than 5,000 applicants, with backgrounds from renowned companies like Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. Our team is guided by the creators of TabPFN and supported by leading AI experts such as Bernhard Schölkopf and Turing Award winner Yann LeCun. Get to know our team here.Looking Ahead: With backing from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are rapidly expanding. This is the perfect moment to join us and help shape the future of structured data AI. Explore our manifesto.

At SoundCloud, we empower artists and fans to connect through the power of music. Established in 2007, SoundCloud is a leading artist-first platform, enabling musicians to build and elevate their careers with cutting-edge tools, services, and resources. With a vast library of over 400 million tracks from 40 million artists, SoundCloud is shaping the future of music.We are actively seeking a Senior Machine Learning Engineer to join our Recommendations Experience team. This role focuses on developing machine learning-driven features that enhance personalization, engagement, and overall satisfaction for our users. In this position, you will leverage strong engineering principles while working across the entire technology stack, from data pipelines and APIs to real-time serving systems. The Recommendations team is responsible for deploying ML-powered features that connect over 200 million users with music tailored to their preferences.In this role, you will take ownership of features from conception to deployment: collaborating with Product and Design teams to understand user needs, architecting data pipelines that process billions of events, and building robust production ML systems that balance performance, cost, and user satisfaction. You will work with technologies such as BigQuery (handling trillions of rows), Airflow orchestration, real-time serving infrastructure (BigTable), and APIs, while engaging in continuous collaboration with Product, Design, Engineering, and Platform teams.Key Responsibilities:Develop, test, and productionize machine learning models.Make informed technical decisions factoring in cost, latency, complexity, and maintainability.Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to create reliable and scalable solutions.

Role Overview Reprisk is hiring a Senior Machine Learning Engineer in Berlin. This position focuses on building and improving machine learning systems that support risk management products. The role centers on strengthening data processing and improving predictive models used throughout the company.

Delivery Hero SE seeks a Principal Machine Learning Engineer to join the Vendor Data Team in Berlin. This position centers on transforming vendor data into insights that support business operations and strategy. Role overview The Principal Machine Learning Engineer will lead efforts to design and deploy machine learning models tailored to vendor data. The goal is to create tools and systems that translate complex information into practical recommendations for the company. What you will do Lead the design and development of machine learning solutions focused on vendor data. Guide the team in using advanced technologies to address real business needs. Convert complex datasets into actionable recommendations that improve operations and support decision-making. Location This role is based in Berlin.