Staff AI Engineer

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 engi…

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 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.

About UsHelsing is a pioneering defense AI company dedicated to safeguarding democracies. Our mission is to achieve technological leadership, ensuring that open societies can maintain sovereignty over their decisions and ethical standards.As advocates for democratic values, we recognize our profound responsibility in the thoughtful advancement and application of transformative technologies like AI. We take this commitment seriously.Our team consists of passionate engineers, AI specialists, and customer-oriented program managers. We are on the lookout for mission-driven individuals to join our European teams and leverage their skills to tackle the most complex and impactful challenges. We foster an open and transparent culture that encourages healthy discussions about the utilization of technology in defense, its advantages, and its ethical considerations.The RoleAt Helsing, we are revolutionizing perception by developing foundational intelligence for the physical world. You will engage in researching, designing, and training large-scale Foundational Models that convert intricate multimodal sensor data into innovative autonomous capabilities.We are in search of an individual who operates at the nexus of AI Research and Machine Learning Engineering, possessing a proven background in LLM/VLM (multimodal) architectures. Your core responsibility will involve training and fine-tuning Vision-Language Models using our proprietary datasets to enhance our diverse product offerings. You will oversee the entire model lifecycle, from data curation and training to evaluation.

About UsHelsing is pioneering the integration of artificial intelligence in defense systems. Our core mission is to safeguard democratic values by providing technological advancements that empower societies to make autonomous decisions and uphold ethical standards.As advocates for democracy, we recognize our unique responsibility to approach the development and implementation of transformative technologies like AI with care and foresight. We are committed to this principle.Our dedicated team comprises engineers, AI specialists, and customer-focused program managers. We seek individuals driven by purpose to join our European teams and leverage their expertise to tackle some of the most intricate and significant challenges. Our culture promotes openness and transparency, encouraging thoughtful discussions on the implications of technology in defense, its advantages, and ethical considerations.The RoleAt Helsing, we are at the forefront of delivering AI-driven capabilities and the supporting infrastructure necessary for semi-autonomous platforms to localize, navigate, and interpret their environment in real-time. You will play a pivotal role in shaping the future of AI within one of the most demanding sectors, where performance must be matched with exceptional generalization capabilities and resilience against adversarial challenges.You will be responsible for developing the autonomous 'brain' for an advanced aerial platform that will actually take flight. Your work will involve integrating state-of-the-art reinforcement learning algorithms into the operational systems of our Unmanned Combat Aerial Vehicle (UCAV), contributing to a transformative military technology.

Delivery Hero is looking for a Senior Python AI Engineer to focus on logistics, data, and machine learning projects in Berlin. This position centers on developing AI-powered tools that support and improve delivery operations. Role overview This role involves designing and building applications using Python, with a strong emphasis on artificial intelligence and data science. The main goal is to create solutions that make logistics processes more efficient and help raise customer satisfaction. What you will do Develop and maintain AI-driven applications tailored for logistics challenges Apply machine learning techniques to optimize delivery workflows Work closely with teams to identify and solve data-related problems Requirements Extensive experience with Python Background in artificial intelligence, data science, and machine learning Ability to build solutions that improve operational efficiency

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 UsAt reliant-ai, we are dedicated to transforming decision-making in an age of overwhelming information. Our mission is to develop the next generation of machine learning software, leveraging generative AI to analyze critical data sources and deliver comprehensive, factual answers to complex inquiries.We believe that the true potential of generative AI can only be achieved by tackling the world's most significant information challenges. With over two decades of expertise in reinforcement learning and natural language processing, we are poised to make a substantial impact in this field.Our team consists of scientists, builders, and entrepreneurs who have pioneered some of the most influential AI applications. Having led teams at industry giants like Google, DeepMind, and EY Parthenon, we now connect cutting-edge AI research with the biopharma sector.

About UsAt Prior Labs, we are pioneers in developing foundation models that effectively comprehend tabular data, which serves as the cornerstone of various fields including science and business. While foundation models have revolutionized the processing of text and images, structured data remains a largely untapped resource. Our mission is to address this $600 billion opportunity, fundamentally transforming the way organizations engage with scientific, medical, financial, and business data.Our Achievements: We proudly stand as the leading organization in the realm of structured data machine learning (ML). Our groundbreaking TabPFN v2 model has been featured in Nature, establishing a new benchmark in tabular machine learning. Following its release, we have significantly enhanced our model capabilities, achieving over 2.5 million downloads and receiving more than 5,500 stars on GitHub. We are witnessing a rapid uptick in adoption from both research and industry sectors as we build the next generation of tabular foundation models and commercialize them with enterprises across Europe and the United States.Our Team: Our team consists of a highly selective group of over 20 engineers and researchers, chosen from a pool of more than 5,000 applicants. We have backgrounds from industry giants such as Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. We are led by the creators of TabPFN and receive guidance from eminent AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet our talented team here.What's Next: Supported by top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are on a rapid growth trajectory. This is an exceptional time to join us and help shape the future of structured data AI. Explore our manifesto for further insight.Core Areas of ImpactAs a member of our engineering team, you will contribute to the development of a novel class of AI models. Our latest innovation, TabPFN, significantly surpasses existing methods by orders of magnitude, and we are just getting started. This is a unique opportunity to:Engage in groundbreaking advancements in AI, rather than just incremental enhancements.Influence the future of how organizations globally manage their most critical data.Join us at an opportune moment: we have secured substantial funding (with announcements imminent), achieved strong initial traction (over 100,000 downloads), and are expanding swiftly.At Prior Labs, we prioritize collaboration and integration of research into practical applications. Our Research Engineers play a critical role in bridging the gap between innovative research and real-world implementation.

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.

JetBrains is seeking a Senior Machine Learning Researcher to focus on Spectrum. This position centers on applying machine learning expertise to improve product features and contribute to ongoing research efforts. Role overview This role involves working with a team dedicated to advancing the capabilities of Spectrum. The Senior Machine Learning Researcher will use their knowledge to influence product direction and participate in research projects that drive innovation. Key responsibilities Apply machine learning methods to enhance Spectrum's technology. Contribute to research initiatives that inform future product development. Share insights and provide leadership within the research team. Locations This position is available in Amsterdam, Belgrade, Berlin, Limassol, Madrid, Munich, Paphos, Prague, Warsaw, and Yerevan.

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 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.

Why Join NebiusNebius is at the forefront of cloud computing, empowering the global AI economy. We provide our clients with essential tools and resources to tackle real-world challenges and revolutionize industries without incurring hefty infrastructure costs or needing to develop extensive in-house AI/ML teams. Our team operates at the cutting edge of AI cloud infrastructure, collaborating with some of the most experienced and innovative leaders and engineers in the industry.Our Work EnvironmentHeadquartered in Amsterdam and publicly traded on Nasdaq, Nebius boasts a worldwide presence with R&D centers across Europe, North America, and Israel. Our diverse team of over 1,400 employees includes more than 400 highly skilled engineers with deep expertise in both hardware and software engineering, complemented by an in-house AI R&D team.About the RoleAs part of Nebius Cloud, which operates one of the largest GPU clouds globally—utilizing tens of thousands of GPUs—Token Factory is dedicated to building a high-performance inference and fine-tuning platform that pushes foundational models to their hardware limits. Our commitment is to enhance throughput, reduce latency, and optimize cost-per-token across our expansive GPU resources.Current Projects You Could Contribute To:Inference Optimization: Identify bottlenecks in LLM inference to accelerate production speed. Maximize performance for a variety of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).Inference Engine Support: Implement innovative speculative decoding architectures, optimize components of different LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.Low Precision Training & Inference: Design and operationalize low-precision training (FP8, NVFP4/MXFP4) and inference pipelines to achieve significant improvements in throughput and cost efficiency.

About Our ClientFounded in Canada in 2015, our client has rapidly expanded to encompass a global portfolio of over 118 companies. They specialize in acquiring and developing vertical market software firms, empowering each business to deliver top-notch mission-critical solutions tailored to their industry's needs. A cornerstone of our client's philosophy is to invest in well-established enterprises while cultivating an entrepreneurial atmosphere that transforms these companies into industry leaders. Their strategic approach focuses on building long-term partnerships with existing management to create and enhance value.About the RoleAs the AI Engineering Lead, you will assume a pivotal leadership role in defining and executing the company's AI strategy. You will be responsible for the practical integration of AI across our client's engineering framework, enhancing internal development and testing processes to improve efficiency and quality. Additionally, you will oversee the development of AI-driven product features that provide tangible benefits to users. In this position, you will ensure alignment between engineering, product management, and data science teams, translating innovative ideas into actionable solutions and guiding teams to unlock their full potential through effective AI integration.Key Responsibilities AI Strategy & Vision: Develop a comprehensive AI roadmap that aligns with business objectives; identify opportunities for AI/ML applications in internal workflows (e.g., code generation, automated testing, monitoring); collaborate with product leadership to design and implement AI-enhanced product features. AI Integration into Engineering Practice: Spearhead the deployment of AI tools within the Software Development Life Cycle (SDLC) (e.g., GitHub Copilot, CodeWhisperer, Tabnine); automate unit testing, static code analysis, and regression testing leveraging AI; guide the application of AI in CI/CD pipelines for improved monitoring, alerting, and predictive operations. AI Product Development: Design and oversee the creation of AI/ML models and AI-enhanced product features; ensure adherence to best practices in AI/ML, including model training, data governance, validation, and ethics; select and manage the necessary infrastructure (e.g., cloud GPU/TPU, model operations platforms like MLflow or Vertex AI). Team Leadership & Cross-Function Collaboration: Lead a team of AI engineers, data scientists, and MLOps personnel; collaborate with product, design, and stakeholders to ensure AI features align with user value; mentor engineering teams on responsible AI usage, prompt engineering, and model comprehension. Governance & Compliance: Establish standards for responsible and explainable AI; ensure compliance with regulatory and ethical guidelines (e.g., GDPR, fairness, transparency); monitor model performance to prevent drift or unintended behaviors.

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.

About UsAt Helsing, we empower machines with advanced AI capabilities that enhance human decision-making and perception. Join us to make a significant impact in a high-stakes environment, where robust AI solutions must meet hardware constraints while defending against adversarial threats.As part of our AI Assurance team, you will pioneer innovative methods for the scalable evaluation of AI products across our organization. Your role will involve designing data collection and experimentation strategies to derive causal insights, thereby promoting responsible decision-making through effective uncertainty quantification and safety protocols.Your Daily ResponsibilitiesYou will define operational domains and assess the reliability of our in-house AI capabilities. Your expertise will help advance the state-of-the-art in uncertainty quantification and calibration. This role requires a deep understanding of our AI systems, enabling you to interface effectively and evaluate their resilience in real-world and adversarial settings. You’ll collaborate on impactful projects with diverse teams, contributing to our mission.

At Veeva Systems, we are dedicated to transforming the life sciences sector through innovative cloud solutions. Our mission is to expedite the delivery of therapies to patients, making a tangible difference in their lives. As one of the fastest-growing SaaS companies ever, we achieved over $3 billion in revenue last year and continue to expand our horizons. Our core values—Do the Right Thing, Customer Success, Employee Success, and Speed—guide our operations. In 2021, Veeva made history by becoming a public benefit corporation, committed to balancing the interests of our customers, employees, society, and investors. As a Work Anywhere company, we value flexibility, allowing you to choose between working from home or in the office, ensuring you thrive in your preferred environment. Join us in revolutionizing the life sciences industry, as we strive to create a positive impact on our customers, employees, and the broader community.The RoleAt Veeva Data Cloud, we offer connected data solutions tailored for Life Sciences, enhancing insights and improving efficiency through a unified data architecture. Our AI team is at the forefront of developing a comprehensive suite of AI tools that empower our global product offerings. Collaborating with over 3,000 data stewards, we combine cutting-edge ML and AI models with human expertise to convert data into actionable insights, speeding up clinical innovation and improving patient access to essential treatments.We are seeking a talented Senior Machine Learning Engineer to join our cross-functional team of data scientists, engineers, and product managers, focusing on the productization and scaling of our AI tools.As a work-anywhere company, you will have the freedom to work from home or the office, emphasizing productivity in an environment that suits you best.