Office Technology Administrator Jobs

As an Enterprise Customer Success Manager, you will proactively drive new product attachment and effective strong relationships across our largest and most strategic customers in Indonesia. You’ll advocate for the customer internally and focus on a positive customer experience. Interactions are rooted in relationship-management, first and foremost, while also advocating for growth opportunities. Enterprise Customer Success Managers follow a well-defined methodology that helps them identify the customer's unique needs and clearly convey the value of the Datadog product. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Partner with Enterprise Account Executive and Solution Engineering teams to onboard, train, and proactively drive adoption with our Enterprise customers in Indonesia. Proactively build relationships with customers to achieve loyalty and advocacy within their organization Collaborate cross-functionally with internal Datadog teams (sales, support, enablement, product, finance, and legal) Own and project manage the on-boarding process for new customers Become a trusted advisor to the client and partner in building a clear and concise plan to meet their business goals Monitor and analyze usage trends to uncover renewal risks and identify opportunity for contract growth/optimization With demonstrated understanding of observability and security platforms, align customers technical and business objectives to our platform offerings Who You Are: Customer-centric with 3+ years in a Customer Success or Account Management role Able to manage a wide portfolio of accounts rolling up to large enterprise corporate accounts Knowledgeable in working with Fortune 1000 companies and global brands across all industries A strong communicator with excep

As an Enterprise Customer Success Manager, you will proactively drive new product attachment and effective strong relationships across our largest and most strategic customers in Indonesia. You’ll advocate for the customer internally and focus on a positive customer experience. Interactions are rooted in relationship-management, first and foremost, while also advocating for growth opportunities. Enterprise Customer Success Managers follow a well-defined methodology that helps them identify the customer's unique needs and clearly convey the value of the Datadog product. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Partner with Enterprise Account Executive and Solution Engineering teams to onboard, train, and proactively drive adoption with our Enterprise customers in Indonesia. Proactively build relationships with customers to achieve loyalty and advocacy within their organization Collaborate cross-functionally with internal Datadog teams (sales, support, enablement, product, finance, and legal) Own and project manage the on-boarding process for new customers Become a trusted advisor to the client and partner in building a clear and concise plan to meet their business goals Monitor and analyze usage trends to uncover renewal risks and identify opportunity for contract growth/optimization With demonstrated understanding of observability and security platforms, align customers technical and business objectives to our platform offerings Who You Are: Customer-centric with 3+ years in a Customer Success or Account Management role Able to manage a wide portfolio of accounts rolling up to large enterprise corporate accounts Knowledgeable in working with Fortune 1000 companies and global brands across all industries A strong communicator with excep

The Infrastructure team builds the foundation we need to support our web and mobile applications, as well as our robust API. We build and operate the software that enables Asana's security, scalability, and speed. Each day, we combine industry best-practices and innovation to support this product-focused company. We're looking for a Junior Infrastructure Software Engineer (New Grad) with a growing passion for Site Reliability and Operability. You will work with a world-class team of engineers on deploying and operating existing systems, and building new ones for challenges that are unique to our problem space. You will have a unique opportunity to learn how to design, develop, and operate services that power Asana, working on projects that help define the future of our infrastructure and how we architect and operate critical services at scale. This role is based in our Reykjavik office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. What You’ll Achieve Learn and Execute: Experience growth and development by being paired with a mentor who will support and guide you through opportunities to stretch and learn. Engineering Craftsmanship: Participate in Asana’s robust technical boot camps to learn our standards for high-quality, maintainable code. You will eventually own specific technical domains through our Areas of Responsibility (AoR) system. Build Foundations: Contribute to projects that define the future of infrastructure for Asana, learning how we architect and operate critical services at scale. Global Collaboration: Partner with other infrastructure teams in San Francisco, New York, and Warsaw to understand and contribute to our service-oriented architecture while navigating cross-timezone workflows. Tooling & Frameworks: Help develop framework

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview: We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space — including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale. The Logistics & ML group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high qu

As an Enterprise Sales Engineer, you will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POVs). Sales Engineers help qualify and close opportunities with customers and partners and have a voice with the product team to help prioritize features based on input from customers, competitors, and partners. At Datadog, we place value in our office culture—the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Partner with the Sales team to articulate the overall Datadog value proposition, vision and strategy to customers Own technical engagement with customers during the trial phase. Communicate Datadog’s value based on activities and work with customers on any identified issues or concerns to successful conclusion Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility Deliver product and technical briefings / presentations to potential clients Maintain accurate notes and feedback in CRM regarding customer input both wins and losses Proactively engage and communicate with customers and Datadog business/technical teams regarding product feedback and competitive landscape Who You Are: Passionate about educating customers on observability risks that are meaningful to their business, and able to build and execute an evaluation plan with a customer Someone with strong written and oral communication skills. This role requires an ability to understand and articulate both the business benefits (value proposition) and technical advantages of our offering Experienced in programming/scripting with any of the following: Java, Python, Ruby, Go, Node.JS, PHP, and .NET etc. Someone with a minimum of 3+ years in a Sales Engineering or DevOps Engineering role Able to sit up to 4 hours, traveling to a

We are looking for an Analyst , who can help us solve a diverse range of tasks, including conducting industry research, analyzing exchange data and mechanisms, and preparing comprehensive analytical reports using Python and other tools. WHAT YOU'LL BE DOING: Analyze trading conditions and rules across multiple exchanges Research and structure diverse exchange mechanisms Organize and maintain gathered information in a clear and structured format Collect and compare market activity statistics across exchanges and asset types Study raw exchange product data Prepare technical tasks for developers Aggregate data from multiple sources using Python Communicate regularly with external counterparties Collaborate with different teams across the company WHAT WE LOOK FOR IN YOU: BS / MS in Economics, Finance, Computer Science, or a related discipline Knowledge of Python and MS Office Good understanding of exchange operations, trading mechanisms, and the landscape of global exchanges and tradable asset types Keen interest in financial markets Strong analytical skills and attention to details Strong time management skills to handle multiple tasks and meet deadlines Proficiency in English Good communication skills, both written and verbal, for effective collaboration with internal teams and external parties Ability to learn quickly and adapt to new challenges WHY SHOULD YOU JOIN OUR TEAM? Diverse range of tasks Great challenge with fast feedback loops Remote from anywhere in the world Access any of our global offices anytime Flexible schedule 40 paid days off

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. This role can be based out of our Toronto or Montreal office or remotely in the Canada while physically based in an Eastern or Central time zone location. The ideal candidate should Have 6+ years of experience working on software development and operating distributed systems Proficiency in Python, Go, or a similar language Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs. Possess a customer-focused mindset Value efficiency in processes and operations Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing) Responsibilities Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineerin

The Team Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, deployment machinery, and observability and alerting systems. The Fabric team manages the infrastructure that enables secure communication between systems and from the public internet. Their responsibilities encompass network architecture, service mesh, and edge load balancing, ensuring customer data remains safe in transit. The team plays a crucial role in developing and maintaining the reliable and globally connected multi-cloud network that supports MongoDB products. This role can sit in our Toronto or Vancouver offices, or fully remote from anywhere in North America. When based in an office, we provide hybrid work accommodation. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As an SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable. The ideal candidate should Have 10+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles Possess a customer-focused mindset, driving improvements that benefit end-users Value efficiency in processes and operations, and display a strong preference for automation over manual processes (“allergic to ops work”) Be intimately familiar with modern cloud-based infrastructure and the network design primitives of at least one of AWS, Azur

The Team Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, deployment machinery, and observability and alerting systems. The Fabric team manages the infrastructure that enables secure communication between systems and from the public internet. Their responsibilities encompass network architecture, service mesh, and edge load balancing, ensuring customer data remains safe in transit. The team plays a crucial role in developing and maintaining the reliable and globally connected multi-cloud network that supports MongoDB products. This role can sit in our NYC HQ, our smaller Austin, Palo Alto, or San Francisco offices, or fully remote from anywhere in North America. When based in an office, we provide hybrid work accommodation. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As an SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable. The ideal candidate should Have 10+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles Possess a customer-focused mindset, driving improvements that benefit end-users Value efficiency in processes and operations, and display a strong preference for automation over manual processes (“allergic to ops work”) Be intimately familiar with modern cloud-based infrastructure and the network design prim

Datadog is entering a new chapter in how our product looks, feels and operates. We're building a small, high-leverage Design Lab team to define that evolution, and we're looking for a Senior Staff Visual Designer to author it. Our design system powers everything we ship. Now we're ready to evolve it. As Datadog expands into AI-driven experiences and more complex product surfaces, the visual language needs to grow with it. This is the role that decides what that language is — someone with taste, judgment, and the confidence to set a direction and defend it. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Define and evolve Datadog’s visual language across product surfaces. Lead exploratory and concept work, creating a range of distinct visual directions for the next generation of the product. Synthesize product context, research, references, and stakeholder input into clear visual principles and a coherent point of view. Establish the quality bar for typography, color, composition, iconography, imagery, motion, and visual expression across the platform. Create high-fidelity product exemplars and prototypes that make an emerging direction tangible. Partner deeply with Brand, Product Design, Motion, and Design Systems to test and refine the direction across different surfaces. Influence executives and senior stakeholders through clear, persuasive visual storytelling. Guide and critique the work of other designers, helping the visual direction remain coherent as it evolves. Help shape how visual exploration, critique, and craft are integrated into Datadog’s design process. You will report directly to the Design Director and work as part of a small, focused team defining the future state before it scales across hundreds of designers and engineers. Who Yo

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into real-time auction actions. Our mission is to maximize realized Advertiser Value by deciding when to participate, how much to bid, and how fast to spend, all while balancing User Experience and Platform Revenue. We are hiring a Senior Applied Scientist II to lead the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production code that makes millions of decisions per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematic

Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, in-person in the London office. Responsibilities: Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. Support deployment and monitoring of search and ranking models in a scalable and performant way. Help build and iterate on RAG pipelines for grounding and answer generation. Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment Experience with Rust will be a plus

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. Open to overseas candidates/Visa Support This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan. The Impact You’ll Make at Appier Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team , which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery. In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing , and personalized content recommendation , while ensuring system robustness and scalability in a dynamic market environment. What You’ll Work On Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes. Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization. Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions. Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning). What We’re Looking For Bachelor’s degree in Computer Science, Mathem

Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools driving high quality and consistent answers, an AI-powered query experience, full governance for data teams, and rich analysis surfaces to present and share the results. You'd be building a zero to one product of what we believe will become a major new product line for Datadog. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you'll do Drive the product vision and roadmap spanning the Data agent experience, the semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets) Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers and other PMs Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions) Design the context and governance layer that makes AI-powered analytics trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops Define how observability data and business data come together to serve unique use cases Engage directly with early customers and internal dogfooding users to iterate on accuracy, usability, and trust Independently research the competitive landscape across legacy BI vendors, warehouse-native analytics, AI-first startups, and AI labs Work on the product pricing Work with GTM teams to define positioning, packaging, and the path to displacing entrenched tools Who you are 5+ years of experience