Role Description We're hiring a Staff MLOps Engineer to own the AI/ML platform at Cint. The immediate focus is supporting the Synthetic Data Platform — models for survey augmentation and respondent profiling — but the role's longer-term remit is broader: Trust Score (our respondent quality and fraud detection model) and other AI/ML initiatives need the same platform capabilities. You'll start by reviewing the current setup and deciding whether to extend it or rebuild parts of it, then build out the shared AI/ML platform from there. You'll report into our Infrastructure and Data Engineering organisation, working in close partnership with the AI/ML team in Prague. This is deliberately a platform-with-feature-focus role: your day-to-day delivery serves the Synthetic Data team's needs, but your architectural remit covers all of Cint's AI/ML workloads. Qualifications - Assess and decide on the current pipeline: - Audit the existing AI/ML training and serving setup. - Decide what's worth building on and what needs to be rebuilt. - Make the call and own the rationale. - Build the shared AI/ML platform: - Training infrastructure, experiment tracking, model registry, serving, monitoring. - Built once, used by Synthetic, Trust Score, and whatever comes next. - Oversee the full ML lifecycle: - From data ingestion and feature processing to annotation workflows. - Ensure the platform facilitates frictionless, rapid model iteration for Data Scientists. - Own training infrastructure on Databricks and Unity Catalog: - Make training fast, reproducible, and traceable. - Lineage matters; reproducibility matters more. - Model serving: - Build the serving layer — low-latency APIs, batch scoring jobs, appropriate caching. - Integrate with our Java/Spring services. - Monitoring and drift: - Build the observability our models need — data drift, model drift, accuracy regression, business metrics. - Grafana dashboards, Prometheus metrics, clear alerts. - Cost and performance: - Set the patterns for cost-effective training and serving. - Represent ML infrastructure spend and ROI credibly to finance stakeholders. - Mentor and multiply: - Act as a force multiplier by coaching AI/ML and Infrastructure engineers on engineering best practices. - You don’t just "do" the work; you set the bar for what "good" looks like. - Drive AI tooling adoption: - Model how AI-native development works for platform teams. - Claude Code, agentic workflows, AI-assisted incident response. - Databricks / Spark Native: - Comfortable in Databricks. - Unity Catalog experience is a strong plus. - Kubernetes & Cloud: - You've deployed ML workloads on Kubernetes. - AWS (EKS) is our environment; familiarity is a plus. - Be a Polyglot: - Python, Scala or Java (for Spark), Kubernetes manifests, Terraform. - AWS or GCP. You move between layers without friction. Requirements - Deep ML Platform Expertise: You've led ML platform work at a serious scale. - Mature Engineering: You’re someone with both a wide and deep background of engineering excellence in a number of disciplines. - Systems Architect: You think about the platform as a product with real users (your ML team). - Technical leader: You lead through standards, RFCs, and credibility — not meetings. - Pragmatic about buy-vs-build: You know when to adopt a managed service and when to build. - Commercially literate: You can justify platform investment to VP / C-suite and translate business priorities into a roadmap. Benefits - Prague-First, Europe-Friendly: Our preferred base is Prague, alongside our existing AI/ML team. - AI-Native Engineering: We're rolling out Claude Code and modern agentic tooling across engineering. - High Autonomy: We trust our engineers to make sound decisions and own their work end-to-end. - Global Impact: Your work powers a marketplace used by millions of people worldwide. Company Description Cint is a pioneer in research technology (ResTech). Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more. The Cint platform is built on a programmatic marketplace, which is the world's largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.

• Lead the design and development of AI/ML, MLOps and Agentic AI solutions; • Develop and optimize machine learning models and pipelines; • Implement LLM-based pipelines; • Deploy models and vector memory systems; • Collaborate with Data Science, Software Engineering and DevOps teams; • Gather requirements from clients and identify technical opportunities; • Ensure clear communication about status and deliveries; • Identify process improvements and automation opportunities; • Maintain production AI and MLOps environments; • Other routine tasks within the area.

• Take a leadership role in shaping the strategic direction of machine learning infrastructure • Identify opportunities for innovation and improvement • Drive the development of cutting-edge solutions for performance, scalability, and reliability of ML systems • Collaborate with Data Science team to ensure seamless deployment of models • Architect and oversee development of complex machine learning pipelines • Manage both real-time and batch inference systems • Mentor and guide mid-level Machine Learning Engineers • Conduct comprehensive code reviews and identify areas for improvement • Communicate effectively with both technical and non-technical stakeholders • Lead integration of new technologies into the infrastructure

Role Description As a Lead Machine Learning R&D Engineer at Matterport, a part of CoStar Group, you will be at the forefront of innovating and advancing our spatial computing platform. You will play a critical role in researching, designing, and implementing cutting-edge machine learning algorithms and models that enhance our ability to digitize the built world, transform physical spaces into rich digital twins, extract valuable insights from them, and create delightful user experiences that make it easy for our customers to modify and interact with their digital twins. This role requires a deep understanding of ML principles, a passion for solving complex real-world problems in 3D data, computer vision, and a desire to contribute to a product that is revolutionizing how people interact with and understand real estate. You will work within a dynamic R&D environment, collaborating closely with fellow engineers, researchers, and product teams to translate groundbreaking ideas into tangible features that empower our users and expand the capabilities of our platform. This is a remote position. Responsibilities: - Conduct cutting-edge research in machine learning, computer vision, and 3D data processing to develop novel algorithms and models for spatial understanding and digital twin creation. - Design, implement, and optimize robust and scalable ML systems and pipelines for processing large-scale 3D datasets, including point clouds, meshes, and images. - Translate research prototypes into production-ready solutions, collaborating closely with engineering teams to integrate ML models into Matterport's core platform. - Evaluate and benchmark model performance, identify areas for improvement, and drive iterative enhancements to our ML capabilities. - Stay up-to-date with the latest advancements in ML research and industry trends, and proactively identify opportunities to apply new techniques to Matterport's challenges. - Collaborate with cross-functional teams including product managers, software engineers, and other researchers to define project requirements, explore technical feasibility, and deliver high-impact features. - Present research findings and technical solutions to internal teams and potentially the broader ML community. - Contribute to the architectural design and strategic roadmap of Matterport's ML systems and research initiatives. - Contribute to the intellectual property of Matterport through patents and publications. Qualifications - Bachelor’s Degree required from an accredited, not for profit university or college. - A track record of commitment to prior employers. - 3+ years of experience in machine learning research and development, with a strong focus on computer vision, 3D data processing, or related areas. - Proficiency in Pytorch and strong programming skills in Python. - Solid understanding of machine learning fundamentals, including deep learning architectures (e.g., CNNs, Transformers), optimization techniques, and evaluation methodologies. - Experience with data manipulation and analysis libraries (e.g., NumPy, Pandas). - Demonstrated ability to conduct independent research, propose novel solutions, and implement them effectively. - Excellent problem-solving skills and the ability to work with complex, real-world datasets. - Strong verbal and written communication skills. Requirements - Ph.D. or Masters Degree in Computer Science, Computer Vision, Machine Learning, Robotics, or a related quantitative field. - 5+ years of industry experience in applied machine learning research and development, particularly with shipping models to production. - Demonstrated expertise in one or more of the following areas: neural rendering (e.g., Gaussian splatting, NeRFs, large reconstruction models, world models), 3D computer vision (e.g., SLAM, 3D reconstruction, point cloud processing, mesh processing), image/video generation models, 2D/3D semantic understanding, depth estimation. - Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices. - Strong track record of publications in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, SIGGRAPH) or significant contributions to open-source projects. - Experience mentoring junior engineers or leading technical projects. - Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to a diverse audience. Benefits - Generous compensation and performance-based incentives. - Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug. - Life, legal, and supplementary insurance. - Virtual and in-person mental health counseling services for individuals and family. - Commuter and parking benefits. - 401(K) retirement plan with matching contributions. - Employee stock purchase plan. - Paid time off. - Tuition reimbursement. - On-site fitness center and/or reimbursed fitness center membership costs (location dependent). - Access to CoStar Group’s Employee Resource Groups. Pay Transparency This position offers an annual pay range from $270,000 - $307,000 determined by relevant skills and experience, and a generous benefits plan.