Role Description Please note: This role requires extensive international travel to our next-gen AI Datacenters. Please do not apply if you are not comfortable with extended periods of travel while on deployments. This role builds on the responsibilities of a Datacenter Deployment Engineer while adding leadership, coordination, and accountability for deployment teams. You will be responsible for planning, organising, and overseeing physical deployments across multiple international DC locations. You will lead teams of 3–5 Deployment Engineers to deliver large-scale GPU infrastructure projects, ensuring high-quality, consistent deployments that follow Nscale’s standards. Responsibilities include validating design plans, ensuring operational readiness, and acting as the senior onsite authority during deployments. Responsibilities - Leadership & Team Coordination - Lead onsite deployment teams (typically 3–5 engineers) across international DC locations. - Coordinate task allocation, provide guidance, and ensure deployment teams work efficiently and safely. - Act as the primary onsite decision-maker and escalation point during deployments. - Mentor and develop Deployment Engineers, promoting best practices and high standards. - Ensure clear communication between field teams, Engineering, Program Management, and DC partners. - Technical Deployment Responsibilities - Plan and oversee layout of IT equipment within datacenters. - Review BOMs and confirm all hardware fits available space while ensuring day-two maintainability. - Validate that datacenter environmental maximums are adhered to: - Power - Cooling - Weight limits - Evaluate BOMs for interoperability, ensuring: - Optics/AOC/DAC are fit for purpose - Customer specifications are met - Nscale project requirements are fulfilled - Produce and validate structured cabling designs. - Define, maintain, and enforce deployment standards across all sites. - Oversee cable pathing, length estimation, procurement, and QC. - Work cross-functionally with Engineering to ensure uniformity of deployments across all regions. - Support initial configuration of firewalls/routers and base switch configuration. - Serve as the onsite subject-matter expert for the full deployment lifecycle. Qualifications - Proven experience leading technical teams in datacenter or infrastructure deployment environments. - Advanced knowledge of structured and fibre cabling. - Strong working knowledge of network/server hardware. - Experience creating and reviewing BOMs. - Significant previous datacenter experience. - Knowledge of CMDB tooling and asset management. - Strong attention to detail and commitment to high-quality execution. - Self-starter with a proactive approach—see a problem, fix a problem mentality. - Excellent communication skills, both written and verbal, with ability to coordinate across multiple stakeholders. - Experience designing and implementing repeatable processes. - Strong documentation and reporting abilities. Nice to Have - Python scripting experience. - Experience working with Infiniband fabrics. - Understanding of fat tree or rail-optimised designs for AI workloads. - Ability to perform performance-level diagnostics on AI fabrics. Benefits - Collaborative, supportive, and innovative environment. - Highly competitive package (base + equity) with reviews every 12 months. - Opportunity to join the fastest-growing tech startup. - Dynamic progression plan tailored to your ambitions. - Human-first flexibility with a remote-first team. Equal Opportunities Statement At NScale, we are committed to fostering an inclusive, diverse, and equitable workplace. We believe that a variety of perspectives enriches our work environment, and we encourage applications from candidates of all backgrounds, experiences, and abilities. We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds. If there’s anything we can do to accommodate your specific situation, please let us know.

• Advise our clients at the intersection of technology and business • Bring stakeholders together through workshops and refine requirements • Design future-proof architectures within consulting engagements • Assume functional and technical project leadership

Title: Generative AI Specialist Location: Remote - United States Job Description: Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for a smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content - Generating labels to advance understanding of a concept, trend etc. - Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: - A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) - Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process.

Role Description - Design and develop enterprise-grade Generative AI and Agentic AI solutions. - Build AI-powered assistants, copilots, and intelligent workflow automation platforms. - Implement and optimize: - Large Language Models (LLMs) - Retrieval Augmented Generation (RAG) - Multi-Agent Systems - Semantic Search architectures - Develop AI orchestration frameworks for autonomous and collaborative AI agents. - Build scalable AI pipelines and microservices using Python and modern AI frameworks. - Design vector search and enterprise knowledge retrieval solutions. - Fine-tune prompts, optimize inference performance, and improve AI response quality. - Develop secure API integrations and event-driven AI architectures. - Collaborate with product, architecture, security, and engineering teams. - Ensure responsible AI governance, security, compliance, and observability standards. - Support deployment, monitoring, and continuous improvement of AI systems in production. Company Description At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. - At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. - Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. - Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself. - We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. - We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace.