Anthony Kelly

Job Title: Senior MLIR Compiler EngineerLocation: Germany About UsBe part of a team building ultra energy-efficient infrastructure for next-generation AI inference. Leveraging dynamic sparsity and brain-inspired computing architectures, we’re pioneering radically more efficient paths for GenAI algorithms. What You’ll DoDesign, implement, and optimize MLIR-based compiler frameworks for our brain-inspired AI hardware.Collaborate closely with hardware and software teams to map dynamic sparsity algorithms efficiently to our architecture.Develop new compiler passes, transformations, and optimizations tailored for energy-efficient AI workloads.Profile and analyze compiler performance to identify and eliminate bottlenecks.Contribute to open-source compiler technologies where applicable. What We’re Looking For4+ years of experience as a compiler engineer or developer, ideally with a focus on MLIR, LLVM, or related frameworks.Strong knowledge of compiler design, intermediate representations, and optimization techniques.Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and their compiler stacks is a plus.Familiarity with hardware-aware optimization (e.g., for GPUs, accelerators, or custom architectures).

A fast-moving team working at the forefront of mobile advertising is looking for a Lead Data Scientist to help shape the future of programmatic monetisation. This role offers the opportunity to work on real-time bidding systems where ads are auctioned and rendered in milliseconds across thousands of mobile apps. The team develops advanced algorithms and data-driven systems that directly compete with some of the biggest names in the industry. With a focus on research-driven innovation, the team aims to balance the needs of users, publishers, and advertisers while maintaining a high-quality user experience. The Lead Data Scientist will be responsible for growing and mentoring a team, driving technical direction, and contributing directly to data science projects. At least half of the role will involve hands-on work, with the remainder focused on leadership, collaboration, and strategic planning. Key ResponsibilitiesBuild and lead a high-performing data science team, including hiring, mentoring, and setting best practicesTranslate business goals into data solutions that strengthen the competitiveness of the ad platformWork on data science tasks individually, contributing significantly to project outcomesDocument experiments, methodologies, and implementation details clearlyCollaborate closely with product, infrastructure, and business teamsContribute to strategic planning and define quarterly and long-term objectivesRequired Skills and ExperienceA degree in mathematics, physics, computer science or equivalent experience in data science (minimum 5 years)At least 2 years of leadership experience, including line management and career development supportStrong programming skills in Python, R, Scala, Julia or similar languagesProven analytical skills and a solution-oriented mindsetExperience working with large-scale data platforms such as AWS Athena, Kafka, Spark, Flink, and S3Expertise in scailing recomendation systemsAbility to explain complex mathematical concepts in simple termsExcellent communication skills and experience working across teamsDesirableExperience building and selecting technologies for a modern data science tech stack (e.g. Airflow, Kafka, Flink)Understanding of MLOps and collaboration with engineering teamsBenefits and PerksHybrid working model with up to two remote days per week and three weeks per year of remote work from anywhere30 days annual leaveComprehensive relocation support including visa assistance, relocation bonus, and reimbursement for language coursesMonthly company lunches, snacks, and fresh pastriesAccess to an in-house gym, personal trainer, and wellness classesFrequent team and company eventsBudget for professional development, training, and certificationsEquity programme for full-time employeesMental health and wellbeing support through a dedicated assistance programme

Why this role matters Lead the design and deployment of enterprise-grade generative AI solutions on Azure. Your work will drive innovation and deliver measurable value across business functions. Responsibilities • Design scalable, secure generative AI architectures using Azure OpenAI Service, Azure ML, Cognitive Services, AKS, and vector databases. • Define and lead AI adoption strategies aligned with business objectives, focusing on text, image, and code generation use cases. • Evaluate, integrate, tune, and operationalise foundation models like GPT, DALL·E, and Codex. • Build automated AI pipelines and MLOps workflows with Azure ML, Data Factory, Synapse, DevOps, and LLM orchestration tools such as LangChain or Semantic Kernel. • Ensure compliance with responsible AI principles, data governance standards and regulatory requirements. • Partner with senior leadership to translate technical concepts into clear business recommendations. • Stay current with generative AI trends and emerging Azure tools; propose new use cases and solutions. Required experience and skills • Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML or related field. • At least seven years of solution architecture experience, including a minimum of two years working hands-on with Azure AI and generative models. • Expertise in Azure OpenAI Service, Azure ML, Cognitive Search, AKS, and vector databases such as Cosmos DB, Pinecone or Weaviate. • Practical experience with LLM orchestration frameworks like LangChain or Semantic Kernel, and with prompt engineering and model fine‑tuning. • Programming proficiency in Python, C# or equivalent, and solid understanding of REST APIs, CI/CD pipelines and DevOps practices. • Preferred certifications: Microsoft Certified: Azure Solutions Architect Expert and/or Azure AI Engineer Associate. What's in it for you?• Competitive base salary with performance-based bonuses. • Flexible working arrangements to support work-life balance. • Opportunities to work on leading-edge generative AI projects with visible business impact. • Access to training, mentoring and support for achieving Azure certifications. • Collaborative, innovative team culture focused on real-world outcomes. What sets you apart Proven ability to deliver tangible results—share past projects where you architected or deployed generative AI solutions, including key metrics and business impact. Demonstrated use of Azure-native tools and best practices in MLOps and responsible AI.

Work on AI and Video Generation as an Applied Research Engineer/AI Engineer. Focus on developing lifelike human avatars without the need for a studio.Title: Senior Research Engineer (Avatars/ Diffusion)Location: Fully RemoteSalary: upto €140,000Responsibilities:Develop cutting-edge CV algorithms for realistic human avatars.work on the lasted Generative AI research initiatives such as Diffusion based models and transformers.Support team in advancing synthetic avatar generation.Requirements:Academic and industry expertise Video Generative AI.2+ years in generative computer vision (GANs, diffusion models, auto-encoders).Proficiency in Python and deep learning libraries (PyTorch, TensorFlow).Expertise in building scalable and maintainable CV algorithms.Take the next step towards an exciting career by clicking the "Apply" button. We look forward to hearing from you!

Opportunity to Join a stealth AI Video Start-up.Role: Founding ML Engineer Location: Berlin (Hybrid)Salary: Upto 130,000Product: AI for ads, replacing the manual production with fully automated, AI-generated content that actually performs.What You’ll Build:Multimodal GenAI systems that turn product descriptions, customer data, or ad briefs into complete video ads—script, visuals, voice, music, and timing.Text-to-video generation pipelines integrating LLMs, diffusion models, and TTS for coherent, on-brand storytelling.Realistic lip-synced avatars and voiceovers to humanize product messaging—matching tone, pacing, and emotion.Automated editing and scene composition tools (e.g. camera motion, transitions, overlays) guided by AI and ad performance data.Scalable ML infrastructure to train, deploy, and serve GenAI models in production.Ideal Experience:Minimum 5 years AI/ ML Experience2+ years relevant GenAI experienceIdeally you have End-to-end experience with multimodal AI; LLMs + diffusion models + audio/video synthesis