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Privacy and Responsible AI Manager
Herzum Software srl Unipersonale

Remote Italy

Welcome to Herzum now part of Catworkx! We are much more than an IT consulting company we are innovators pioneers and partners in excellence. Today we begin a new chapter as part of the catworkx group — one of the world’s leading Atlassian Platinum Partners with a strong presence across Europe. Founded in Chicago in 2000 Herzum has grown into an international organization with offices in Italy the United States India Switzerland Ecuador and the United Kingdom. Together with catworkx we combine expertise culture and vision to deliver solutions that bring innovation efficiency and collaboration to companies around the world. We specialize in Agile DevOps and team collaboration technologies helping organizations work better faster and more seamlessly. Privacy and Responsible AI Manager We are seeking a Privacy and Responsible AI Manager. The role will be part of a global team providing advisory and compliance support to a broad range of internal stakeholders. The selected candidate will primarily support business functions ensuring that Privacy Responsible AI and data regulations are embedded by design into business decisions processes and initiatives. Key activities include Acting as a primary global advisor to internal functions influencing strategy to ensure privacy Responsible AI and data regulations are embedded into business decisions Supporting Privacy by Design and Assurance activities across global data processing initiatives Managing privacy impact assessments and supporting privacy demand management through OneTrust Leading the implementation of privacy and Responsible AI principles across global data processing activities Owning and managing PIAs AI risk assessments and demand management activities to ensure continuous regulatory compliance Partnering with local market teams to align with global privacy and AI risk requirements while considering regional regulatory variations Collaborating with Group Cyber Security to integrate privacy and Responsible AI principles into global risk assessments from the outset Providing advice across areas such as commercial marketing adtech cookie management consumer IoT big data Responsible AI HR and finance processes Supporting the investigation and management of personal data breaches and incidents including advice documentation stakeholder coordination reporting and remediation Required Technical Skills Strong experience in privacy ideally gained in the telecommunications sector or another relevant business area In-depth knowledge of GDPR the ePrivacy Directive and related jurisprudence Working knowledge of the EU AI Act and data regulations Strong understanding of the global privacy landscape particularly in relation to products services and processes Familiarity with compliance management standards tools methodologies and best practices Excellent organisational skills with the ability to manage multiple requests priorities and stakeholder needs Previous experience with OneTrust would be highly relevant given the role’s focus on privacy demand management and assessment workflows Work mode Fully remote. We are looking for VAT-registered professionals (Partita IVA) available to collaborate with a daily rate between € 260 and € 280. Join Us! Become part of a team driven by innovation belief in talent and a commitment to excellence. Your next career step starts here. This announcement is addressed to both sexes in accordance with Laws 903/77 and 125/91 and to people of all ages and nationalities in accordance with Legislative Decrees 215/03 and 216/03.

New 30 min(s). ago 🔥 View
Catalog Analyst-Intern
Editorialist

Remote Italy

What’s Editorialist? Editorialist melds personal styling editorial content and shopping into one seamless digital experience powered by proprietary technology and e-commerce tools. Editorialist.com our media property delivers sophisticated content and commerce to aspirational and affluent consumers. Our stories connect readers with bespoke product and service solutions for fashion accessories beauty and wellness needs. The cornerstone of our tech platform—the YX app—blends content digital services and e-commerce for our elite clientele individuals with an average net worth in excess of $550 million. Our co-founder and CEO Rafael Ortiz previously co-founded NexTag the largest comparison shopping site for products and services and was responsible for marketing and business development until its sale for $1.2 billion Job synopsis We need a Catalog Analyst - Intern to help clean and manually curate our 1 million+ products and help with the feedback pipeline to improve machine learning algorithms. ### Responsibilities Manually review predictions of our machine learning models and provide feedback. New Product addition to the catalog. Merging of similar products from different retailers from the catalog. Curating and tagging best-selling products based on current market trends involving style color print pattern and silhouettes Correct the product descriptors sub-categories and subtypes. Maintain categorization of the products. Catalog sanitization of different categories and adding up new attributes for better visibility of the product. ### Requirements Bachelor’s degree or current student(preferably related to fashion). High Energy/Startup Mindset Willing to learn. Past exposure to the US Fashion Market is a big plus. We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.

New 30 min(s). ago 🔥 View
Staff Storage Platform Engineer (AI Storage) - Radian Arc
Submer

Remote Italy

About Radian Arc. Radian Arc provides an infrastructure-as-a-service (IaaS) platform for running cloud gaming artificial intelligence and machine learning applications inside telecommunication carrier networks. Our teams across the USA Australia Central Europe Malaysia Singapore and Japan offer telecom operators a GPU-based edge computing platform without the need for capital expenditure facilitating low latency and improved economics for value-added services and the monetization of 5G investments. What impact you will have Mission Design build and operate the AI storage layer powering large-scale GPU infrastructure enabling datasets model artifacts checkpoints and inference state to be delivered to compute clusters with extremely high throughput and predictable latency. You will play a key role in architecting and evolving the storage platform across edge and core deployments supporting the full lifecycle of AI workloads including distributed inference fine-tuning and large-scale model training. The role spans multiple storage architectures used across the platform including hyperconverged storage currently based on StorPool local NVMe storage for latency-sensitive workloads and edge deployments and disaggregated AI storage platforms such as VAST Data and Weka. As the first dedicated storage platform role in the organization this position combines Staff-level architectural ownership technical direction and cross-functional influence with hands-on execution across storage design deployment performance engineering troubleshooting platform integration and operational improvement. A key responsibility of this role is designing and optimizing the storage architecture underlying distributed inference stacks such as NVIDIA Dynamo llm-d or similar inference orchestration frameworks. This includes ensuring that storage systems efficiently support inference workloads through optimized dataset access model artifact distribution checkpoint handling and KV-cache persistence. You will design scalable storage systems capable of feeding thousands of GPUs while balancing throughput latency resilience and cost efficiency and work closely with compute networking and platform engineering teams to ensure seamless integration with the platform orchestration layer. Because this is currently the primary storage platform role in the company the position is intentionally hybrid you are expected to operate at L6 / Staff in terms of long-term design standards cross-team influence and platform direction while also directly executing critical storage work that in a larger organization would be distributed across multiple engineers. What you'll do ### Storage Architecture Design scalable AI storage architectures supporting both edge and core deployments. Define storage strategies for distributed inference fine-tuning and training workloads. Architect solutions across multiple storage models + Hyperconverged infrastructure such as StorPool + Local NVMe storage + Disaggregated storage systems such as VAST Weka and related architectures. Define reference architectures design principles and reusable patterns for storage platforms so future deployments follow standards rather than one-off implementations. Evaluate trade-offs across throughput latency resilience data locality cost and operability and make clear recommendations to engineering and leadership. Influence the long-term storage roadmap including architecture choices for edge core hyperconverged and disaggregated environments. ### AI Workload Optimization Optimize storage throughput and latency for GPU-heavy clusters. Design data locality strategies to minimize dataset movement across the network. Benchmark storage performance under real AI workloads. Optimize I/O patterns for large dataset ingestion checkpointing and model artifact distribution. Work directly with compute teams to ensure storage architecture matches the access patterns of distributed training fine-tuning and inference frameworks. Establish performance baselines and validation methods so storage platforms are tested against realistic AI workload behavior rather than only synthetic benchmarks. ### Platform Integration Implement and maintain CSI drivers. Integrate storage platforms with Kubernetes and orchestration systems. Integrate block object and shared file storage into the platform. Design multi-tenant storage architectures supporting isolated workloads. Ensure storage capabilities are correctly exposed into platform services workload orchestration and lifecycle automation. Define standards for how storage should be integrated into Kubernetes-based and platform-managed environments across different deployment models. ### Distributed Storage Systems Contribute to the design of exabyte-scale storage platforms. Support S3-compatible object storage distributed file systems and block storage. Integrate storage clusters into heterogeneous customer environments. Design storage systems with clear fault domains lifecycle management approaches scaling paths and operational boundaries. Define reusable operating patterns for multi-cluster and multi-site storage environments. ### Distributed Inference Storage Architecture Design the storage architecture supporting distributed inference platforms such as NVIDIA Dynamo llm-d or similar frameworks. Optimize storage performance for large-scale LLM inference workloads. Design efficient strategies for KV-cache persistence and retrieval using distributed storage platforms such as VAST or Weka. Optimize storage access patterns for token generation pipelines and high-concurrency inference workloads. Ensure inference infrastructure scales efficiently across thousands of GPUs. Partner with platform and inference teams to ensure storage design supports evolving inference architectures and avoids becoming a bottleneck in throughput latency or concurrency. ### AI Data Path Optimization Design high-performance data paths between GPU clusters and distributed storage. Optimize performance using technologies such as + GPU Direct Storage + RDMA / RoCE + NVMe-oF. Ensure predictable latency for inference serving workloads. Define architectural approaches for storage-to-GPU data movement that balance performance gains with operational complexity and deployment practicality. ### Performance Engineering Work with technologies such as the following to maximize data throughput to GPU clusters. + RDMA + RoCE + GPU Direct Storage + SPDK + NVMe-oF Lead storage performance investigations across hardware network OS filesystem and workload interaction points. Drive systematic tuning of storage paths for large-scale GPU environments and define repeatable validation and benchmarking approaches for future deployments. ### Reliability & Operations Improve the reliability durability and observability of the storage stack. Collaborate with operations teams to monitor storage systems using telemetry and metrics. Optimize performance latency and resilience of storage infrastructure. Lead incident response and root-cause analysis for major storage events and chronic performance issues. Translate operational pain points and incidents into durable design changes standards runbooks and architectural improvements. Establish measurable benchmarks for storage reliability performance consistency recovery behavior and operability across deployments. ### Engineering Execution & Delivery Lead end-to-end engineering delivery of storage infrastructure from architecture and validation through production rollout. Support practical implementation of storage platforms in both new deployments and existing environments. Validate storage BOMs and architecture assumptions together with infrastructure compute and deployment teams. Contribute detailed input into datacenter layouts node profiles and storage topology decisions. Drive scaling strategies capacity planning and storage lifecycle decisions. Ensure storage changes are executed safely with minimal customer impact. Act as both the architectural owner and the practical execution lead for critical storage initiatives during the build-out phase of the storage function. ### Cross-Team Collaboration Work closely with compute networking platform DevOps and operations teams. Ensure storage integrates seamlessly into the AI platform architecture. Act as the primary storage design authority across the organization guiding adjacent teams on how storage constraints and capabilities should shape platform decisions. Communicate architectural decisions trade-offs risks and operational implications clearly to stakeholders. Share knowledge and mentor engineers on high-performance storage design. Raise the technical bar by helping adjacent teams better understand storage behavior in distributed AI environments. Technical Stack - CSI. NVMe / NVMe-oF. Distributed file systems. Object storage. Linux storage stack. RDMA / RoCE. GPU Direct Storage. SPDK. StorPool. VAST Data. Weka. MinioFS. Rook Ceph. What you'll need ### Core Experience Strong hands-on experience designing and operating distributed storage systems for high-performance compute environments. Proven experience designing storage architectures for large-scale AI inference or training platforms including dataset distribution checkpointing and KV-cache storage patterns. Deep knowledge of the Linux storage and I/O stack. Strong understanding of AI workload data access patterns. Experience optimizing storage for GPU-accelerated workloads. Familiarity with Kubernetes storage integrations such as CSI. Experience operating large-scale storage clusters. Experience owning both architecture and direct implementation in lean or fast-scaling environments is strongly preferred. ### Advanced AI Storage Expertise The candidate should have deep expertise in designing and operating storage platforms optimized for GPU-heavy environments and distributed AI workloads. This includes a strong understanding of how training fine-tuning and inference systems interact with storage and how storage architecture affects throughput latency concurrency checkpoint recovery dataset distribution and serving performance. Relevant expertise includes Strong understanding of storage access patterns for distributed inference and training. Experience designing storage platforms that support large dataset ingestion and model artifact distribution at scale. Practical experience tuning storage architectures for checkpointing distributed file access object access and high-concurrency inference. Familiarity with storage patterns for KV-cache persistence and retrieval. Experience optimizing data locality and reducing unnecessary network movement between storage and compute. Understanding of how storage performance affects large-scale AI frameworks model-serving systems and inference orchestration layers. ### Systems & Troubleshooting Ability to debug complex cross-layer issues spanning + Storage hardware + Networking + Linux kernel and I/O paths + Filesystems + Object and block storage layers + Kubernetes integrations + Distributed workload behavior. Strong knowledge of storage hardware NVMe devices storage fabrics and high-performance data paths. Experience designing storage observability systems. Strong ability to act as the senior escalation point for ambiguous high-impact and multi-domain technical issues. ### Automation Strong automation skills using Python and/or Bash. Experience applying software engineering practices to storage automation and operational tooling. Experience building reusable tooling standards validation patterns or lifecycle automation that increase leverage across teams. ### Leadership Proven ability to lead complex technical initiatives across teams. Comfortable collaborating across engineering operations deployment teams vendors and platform stakeholders. Strong systems-level thinking balancing performance reliability scalability operability and cost efficiency. Demonstrated ability to set architectural direction and drive adoption of engineering standards across an organization. Proven ability to lead through technical influence across multiple teams and domains without relying on formal people management authority. Strong mentoring capability and ability to raise the technical level of adjacent engineering teams. Able to balance short-term execution needs with long-term platform design operational sustainability and cost efficiency. What we offer Attractive compensation package reflecting your expertise and experience. A great work environment characterised by friendliness international diversity flexibility and a hybrid-friendly approach. You'll be part of a fast-growing scale-up with a mission to make a positive impact offering an exciting career evolution. Our job titles may span more than one job level. The actual base pay is dependent on a number of factors such as transferable skills work experience business needs and market demands. Our inclusive responsibility Radian Arc is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion gender gender identity or expression sexual orientation national origin genetics disability age veteran status or any other protected category under applicable law.

New 34 min(s). ago 🔥 View
Tech Talent per progetti Enterprise | AI Area
Digital Rebels

Remote Italy

Digital Rebels è un network di consulenti digitali che supporta grandi aziende e organizzazioni complesse nelle aree Coding Design AI e Data. Affianchiamo i nostri clienti con competenze su misura e supporto operativo flessibile contribuendo alla realizzazione di progetti digitali innovativi e ad alto impatto. Chi stiamo cercando Per supportare la crescita del nostro network vogliamo entrare in contatto con professionisti interessati a collaborare su progetti enterprise prodotti digitali e iniziative innovative in ambito digitale. AI Engineer Machine Learning Engineer LLM Engineer AI Automation Specialist AI Product Manager AI Strategist Conversational AI Designer Soft Skills Problem solving e approccio analitico Capacità di lavorare in team Autonomia operativa Attenzione alla qualità del lavoro e orientamento ai risultati Buone capacità comunicative Cosa offriamo Collaborazioni freelance con Partita IVA Progetti enterprise e digitali ad alto impatto Possibilità di lavoro full remote o ibrido Accesso a un network di professionisti altamente qualificati Coinvolgimento su tecnologie innovative e progetti evolutivi Opportunità continuative in base a competenze e disponibilità Modalità di lavoro Remote / Hybrid (in base al progetto) Nota importante Siamo interessati a professionisti con competenze verticali e approccio concreto ai progetti. Non cerchiamo semplicemente “skill sulla carta” ma persone capaci di portare valore reale all’interno dei team e delle iniziative su cui lavoriamo. Retribuzione €20000 - €28000 al giorno Sede di lavoro Da remoto

New 34 min(s). ago 🔥 View
Tech Talent per progetti Enterprise | Coding Area
Digital Rebels

Remote Italy

Digital Rebels è un network di consulenti digitali che supporta grandi aziende e organizzazioni complesse nelle aree Coding Design AI e Data. Affianchiamo i nostri clienti con competenze su misura e supporto operativo flessibile contribuendo alla realizzazione di progetti digitali innovativi e ad alto impatto. Chi stiamo cercando Per supportare la crescita del nostro network vogliamo entrare in contatto con professionisti interessati a collaborare su progetti enterprise prodotti digitali e iniziative innovative in ambito digitale. Full Stack Developer Frontend Developer Backend Developer Mobile Developer DevOps Engineer Cloud Engineer Software Architect Cybersecurity Engineer Soft Skills Problem solving e approccio analitico Capacità di lavorare in team Autonomia operativa Attenzione alla qualità del lavoro e orientamento ai risultati Buone capacità comunicative Cosa offriamo Collaborazioni freelance con Partita IVA Progetti enterprise e digitali ad alto impatto Possibilità di lavoro full remote o ibrido Accesso a un network di professionisti altamente qualificati Coinvolgimento su tecnologie innovative e progetti evolutivi Opportunità continuative in base a competenze e disponibilità Modalità di lavoro Remote / Hybrid (in base al progetto) Nota importante Siamo interessati a professionisti con competenze verticali e approccio concreto ai progetti. Non cerchiamo semplicemente “skill sulla carta” ma persone capaci di portare valore reale all’interno dei team e delle iniziative su cui lavoriamo. Retribuzione €20000 - €28000 al giorno Sede di lavoro Da remoto

New 34 min(s). ago 🔥 View

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