Field Security Specialist Jobs

About the Role The Agents team investigates how to build, align, and scale frontier AI systems that can tackle complex, multi-step tasks and workflows across text and speech, with a particular focus on agentic and scientific domains. Our work sits at the intersection of agent capabilities, human-computer interaction, and infrastructure—from designing post-training methods for agentic behavior to developing evaluation frameworks for open-ended tasks where traditional metrics fall short. As a research intern, you will work on problems at the frontier of agentic AI, where challenges in alignment, reliability, and scalability are deeply intertwined. Projects may involve developing new training recipes for self-learning and long-horizon reasoning, curating datasets for non-deterministic scientific and agentic tasks, studying failure modes in agentic behavior, or building infrastructure that enables agent operations at scale. You'll operate in a space where algorithmic innovation, dataset and interaction design, and systems work come together to push the boundaries of what AI agents can reliably accomplish. Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Communicate the plans, progress, and results of projects to the broader team Requirements Currently pursuing a Ph.D. degree in Computer Science, Electrical Engineering, Information Science, or a related field Publications at leading ML, NLP, or speech conferences or journals (such as NeurIPS, ICML, ICLR, *ACL, EMNLP, Interspeech) Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Understanding of how LLMs work Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Example Research Directions Training, develo

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet's AI go-to-market runs on a simple conviction: the work is the intelligence. The most credible voice in that conversation isn't a marketer who studied the use cases - it's a practitioner who built them. Someone who has run a real enterprise operation on Smartsheet at scale, pushed the platform past its documented edges, wired it into AI workflows before the playbook existed, and can stand in front of a room of skeptical operators and make them lean in. This role sits at the intersection of product marketing, technical storytelling, and field engineering. You'll translate our AI roadmap into narratives the field can sell, prove those narratives with working demonstrations you build yourself, and represent the practitioner's voice in how we position, package, and activate AI across our customer base. This full-time position reports to the VP of AI Market Strategy and can be located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer. You Will: Own the practitioner narrative. Turn Smartsheet's AI capabilities — MCP, agentic workflows, connected context — into positioning and use cases grounded in how work actually gets done. Operator-to-operator storytelling backed by things you've built. Carry the story externally. Customer sessions, analyst conversations, community engagement, executive briefings. You'll be one of the most visible technical voices in Smartsheet's AI story, with the depth to survive the Q&A. Build what you preach. Worki

Linux Engineer A Career with point72’s Technology team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Support, maintain, and troubleshoot Linux systems in production and development environments Assist with system provisioning, configuration, and lifecycle management Monitor system performance, availability, and capacity; respond to incidents and outages Work closely with developers and quants to support research and trading workloads Automate operational tasks using scripting and configuration management tools Assist with patching, upgrades, and vulnerability remediation Maintain documentation and operational runbooks Participate in on-call rotation (as appropriate for level) What’s REQUIRED Bachelor’s degree in computer science, information technology, engineering, or a related field. 5+ years of professional experience administering Ubuntu Linux systems and ZFS Strong understanding of Linux fundamentals including processes, memory, CPU, filesystems, and networking as well as systemd, cron, logging, and package management (apt) Experie

Overview The Insights team delivers high-quality research, market intelligence, and data-driven analysis to support clients’ strategic and investment decisions. Working across industries-including healthcare and medtech-the team combines primary and secondary research with deep analytical capabilities to generate actionable insights. Team members collaborate closely with global stakeholders to translate complex information into clear, impactful outputs. The Project Manager – Insights is responsible for overseeing the end-to-end delivery of research projects, ensuring timelines, quality standards, and client expectations are consistently met. This role coordinates across internal teams and stakeholders to manage multiple concurrent projects, streamline workflows, and drive execution. The ideal candidate combines strong organizational and communication skills with an ability to translate complex project requirements into efficient delivery. This is a hybrid position out of our Mumbai OR Pune office What You’ll Do : Manage end-to-end delivery of research and insights projects, ensuring timelines and quality standards are met Coordinate across analysts, researchers, and stakeholders to execute project plans Define project scope, objectives, and deliverables in collaboration with internal teams and clients Track project progress, manage risks, and proactively address bottlenecks Oversee preparation and delivery of client-ready reports, presentations, and outputs Ensure consistency, accuracy, and quality of insights and deliverables Optimize workflows, processes, and tools to improve efficiency and scalability Support resource allocation and prioritize workload across multiple concurrent projects Maintain clear and consistent communication with stakeholders on timelines and outcomes What You Have : Bachelor’s degree from an accredited college/university (e.g., Business, Economics, Life Sciences, or related field) +4 years of experience in project management, consulting, r

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Inventory Manager – High Value Devices Function: Operations – Asset & Inventory Control Inventory Type: High-Value Electronic Assets Tools Used: Manual Registers & Google Sheets Work Mode: On-site Role Overview The Inventory Manager will be responsible for end-to-end custody, tracking, and reconciliation of high-value inventory, primarily iPhones and related accessories such as SD cards and card readers. This role demands strict control, zero tolerance for mismatches, and complete documentation discipline. No inventory movement is allowed without entries, and physical stock must always tally with records. (Morning Shift - 7 am to 4 pm; Evening Shift - 4 pm to 2 am) Key Responsibilities 1. High-Value Inventory Ownership Take complete ownership of high-value devices and accessories . Ensure serial-number–level tracking for all devices. Maintain zero loss and zero undocumented movement . 2. Inward Inventory Management (IT → Inventory) Receive devices and accessories from the IT team. Verify: Quantity Serial numbers Physical condition Record all inward movements immediately in: Manual registers Google Sheets Escalate any mismatch, damage, or discrepancy without delay. 3. Outward Inventory Management (Inventory ↔ Field Ops) Hand over inventory from: Inventory to Field Ops (FO) Field Ops back to Inventory Ensure no item goes out without prior entry . Capture details including: Item name and serial number FO name / ID Date and time of handover Expected return date Avoid

About the role The world is moving fast — and AI is moving faster. As a Product Marketing Manager focused on AI at Sigma, you'll be at the tip of the spear, helping define how we tell the story of one of the most exciting areas of the product. This role is as much about clarity as it is about creativity: you'll take complex, fast-evolving AI capabilities and distill them into the market messages, sales narratives, and customer stories that make people say "I get it — and I want it." We're looking for someone with genuine intellectual curiosity about AI, a bias for action, and exceptional instincts for what makes a message land. If you can absorb a lot of information quickly, find the signal in the noise, and write messaging that moves people — this role is for you. What you'll do Develop and refine positioning and messaging for Sigma's AI features, working closely with the Director of Product Marketing, AI and the Product team. Create sales enablement content — one-pagers, battlecards, demo guides, and objection handlers — that help the field confidently sell Sigma's AI capabilities. Support product launches for AI features: coordinate across product, design, marketing, and sales to bring new capabilities to market clearly and effectively. Research competitors' AI positioning and identify opportunities to sharpen Sigma's differentiation. Write and contribute to thought leadership content, blog posts, and customer-facing collateral that educate the market on Sigma's AI vision. Gather and synthesize customer and prospect insights — from win/loss data, customer interviews, and sales calls — to continuously improve messaging. Partner with demand generation and content teams to ensure AI messaging is consistently represented across campaigns, website, and events. What we're looking for 3+ years of product marketing experience in B2B enterprise software and/or cloud data platforms. The ability to learn quickly and deeply — you can get up to speed on a new te

About the Role The Agents team investigates how to build, align, and scale frontier AI systems that can tackle complex, multi-step tasks and workflows across text and speech, with a particular focus on agentic and scientific domains. Our work sits at the intersection of agent capabilities, human-computer interaction, and infrastructure—from designing post-training methods for agentic behavior to developing evaluation frameworks for open-ended tasks where traditional metrics fall short. As a research intern, you will work on problems at the frontier of agentic AI, where challenges in alignment, reliability, and scalability are deeply intertwined. Projects may involve developing new training recipes for self-learning and long-horizon reasoning, curating datasets for non-deterministic scientific and agentic tasks, studying failure modes in agentic behavior, or building infrastructure that enables agent operations at scale. You'll operate in a space where algorithmic innovation, dataset and interaction design, and systems work come together to push the boundaries of what AI agents can reliably accomplish. Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Communicate the plans, progress, and results of projects to the broader team Requirements Currently pursuing a Ph.D. degree in Computer Science, Electrical Engineering, Information Science, or a related field Publications at leading ML, NLP, or speech conferences or journals (such as NeurIPS, ICML, ICLR, *ACL, EMNLP, Interspeech) Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Understanding of how LLMs work Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Example Research Directions Training, develo

Role Overview As a Research Intern in the Model Shaping team, you will work on one or more of the following areas: Advanced post-training methods across supervised learning, preference optimization, and reinforcement learning New techniques and systems for efficient training of neural networks (e.g., distributed training, algorithmic improvements, optimization methods) Robust and reliable evaluation of foundation model capabilities The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. Past research led by Model Shaping interns resulted in the following publications: Escaping the Verifier: Learning to Reason via Demonstrations (ICML 2026) Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking (ICML 2026) ​​ FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models (ICLR 2026) Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Integrate the research results into Together products Requirements Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Familiarity with the Transformer architecture and recent developments in foundation models Preferred Requirements Prior research experience with training foundation m

Role Overview As a Research Intern in the Model Shaping team, you will work on one or more of the following areas: Advanced post-training methods across supervised learning, preference optimization, and reinforcement learning New techniques and systems for efficient training of neural networks (e.g., distributed training, algorithmic improvements, optimization methods) Robust and reliable evaluation of foundation model capabilities The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. Past research led by Model Shaping interns resulted in the following publications: Escaping the Verifier: Learning to Reason via Demonstrations (ICML 2026) Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking (ICML 2026) ​​ FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models (ICLR 2026) Responsibilities Research and implement novel techniques in one or more of our focus areas Design and conduct rigorous experiments to validate hypotheses Document findings in scientific publications and blog posts Integrate the research results into Together products Requirements Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Familiarity with the Transformer architecture and recent developments in foundation models Preferred Requirements Prior research experience with training foundation m

About The Role The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems. As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads. Responsibilities Design and conduct rigorous experiments to validate hypotheses Communicate the plans, progress, and results of projects to the broader team Document findings in scientific publications and blog posts Requirements Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Preferred Qualifications Prior research experience in foundation models , efficient machine learning , or ML systems . Publications at leading conferences in machine learning or systems (i.e., ML

About The Role The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems. As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures. Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads. Responsibilities Design and conduct rigorous experiments to validate hypotheses Communicate the plans, progress, and results of projects to the broader team Document findings in scientific publications and blog posts Requirements Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field Strong knowledge of Machine Learning and Deep Learning fundamentals Experience with deep learning frameworks (PyTorch, JAX, etc.) Strong programming skills in Python Familiarity with Transformer architectures and recent developments in foundation models Preferred Qualifications Prior research experience in foundation models , efficient machine learning , or ML systems . Publications at leading conferences in machine learning or systems (i.e., ML

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Business Development Manager - Newcastle Join us in our mission to transform the way people shop and eat, where impact, innovation, and growth drives everything we do. Our Commercial team sits at the centre of Deliveroo’s marketplace—shaping how we serve restaurants, grocers, and new verticals worldwide. From negotiating key partnerships to unlocking new revenue streams and crafting data-led growth strategies, we take on big challenges that move the business forward. If you thrive in fast-paced, commercial environments and want to influence the future of a global brand—this is the team for you. We’re looking for a Field Sales Executive to join our Newcastle team. This is a hybrid role. In this role, you’ll help us build relationships with new restaurant partners across the region, improving our proposition for customers and identifying ways to continue our fast growth. Get to know our Commercial team — what drives us, how we work, and what you can expect. What You’ll Be Doing You’ll be joining the Regional UK and Ireland team. The Regional UK and Ireland team drives Deliveroo's performance across all 4 nations of UKI. From Brighton, to Bognor to Belfast, we are experts in the local markets we serve, focusing on bringing the best possible selection to our customers and opportunities for growth to our partners. Here’s what your day-to-day might look like: Drive regional restaurant acquisition: Map, prospect, pitch, and close high-value restaurant partners across your region to expand our local market selection. Execute strategic business development: Engage with independent restaurants via physical visits, emails, calls, and social platforms to demonstrate the commercia

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. About the role: You would work on real hardware, not simulators: racks of pre-release APs and switches, RF test equipment, and the automation that gates every release. You will spend your time finding out why a link negotiated at 100M instead of 10G, why a client did not roam cleanly between APs, or why PoE came up wrong after a reboot, and then building the automated test that catches it next time. Responsibilities: Validate WiFi and switching firmware on pre-release hardware in our lab; Build and maintain the automated test suites that gate firmware releases; Investigate failures down to root cause and escalate to firmware owners with evidence; Turn each recurring field issue into permanent regression coverage; Extend our lab tooling and CI pipelines. Requirements: 2+ years of experience with Python; Solid networking fundamentals: VLANs, routing, WiFi, firewalls; Experience with CI (Jenkins or similar) and Linux/Bash; Experience with AI tools - Claude, Codex, etc; Fluent in English and Latvian. Nice to have: Experience with Jenkins DSL (Groovy), JavaScript, Terraform; Network or system administration background; Embedded or hardware test experience; RF or wireless testing background. Benefits: International work environment and work with global development teams; Ability to deliver software that is used by millions of peo

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. About IRL (Instawork Robotics Labs) Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . What you’ll do Lead Workforce & Operations: Drive day-to-day workforce management for Clippers, Graders, Regraders, SMEs, and ICs across shifts/sites, optimizing staffing, capacity planning, and throughput against SLA targets. Implement Quality Systems & Methods: Maintain the QMS and apply structured methods (RCA, CAPA, FMEA, 8D, SPC) to address recurring defects, calibration drift, gold-sample injections, and consensus checks. Own SOPs & Process Standards: Build, version-control, and continuously iterate SOPs for existing and new program launches, ensuring floor adoption and structured QA onboarding/re-calibration paths. Bridge Cross-Functional Teams: Translate engineering data requirements into floor-executable QA criteria, report field issues back with evidence, and represent QA in program launches and crisis calls. Drive Data-Led Quality: Monitor and analyze key QA metrics—defect/reject rates, inter-grader agreement (ka

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the role We’re hiring the first AI Deployment Manager to partner with some of our most strategic enterprise customers. As an AI Deployment Manager, you’ll drive adoption, deliver measurable business value, and help shape how AI transforms engineering teams. You’ll act as the connective tissue between customer stakeholders and our internal teams, influencing both the Cursor roadmap and each customer’s implementation strategy. This role is highly cross‑functional and customer‑facing. You understand software development workflows, care deeply about developer tools, and love helping engineering organizations succeed at scale. What you'll do Build and grow deep relationships with engineering leaders and power users at key accounts Partner with Field Engineering and Sales to deliver a seamless post‑sale experience Drive adoption of Cursor by aligning usage with business objectives and engineering goals Guide customers on best practices for rollout, prompt strategy, context configuration, and internal enablement Serve as the customer’s voice internally and influence roadmap priorities Provide strategic account planning and regular business reviews with VP‑ and CTO‑level stakehold