Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a
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Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross-functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams. This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management. It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole. Please Note: The existing team work in offices in London, Edinburgh, Pa
Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology. Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI. July 31st 2025 - Cohere's Multimodal team Introduced Command A Vision: Multimodal AI Built for Business. At release our new flagship vision-language model: ● Consistently outperforms major models like Llama 4 Maverick, Mistral Medium/Pixtral Large, and GPT4.1 ● 83.1% average benchmark (73.5% MathVista, 90.9% ChartQA...) ● Built for the real world - 112B parameters running on just 2 GPUs ● Open weights live on HuggingFace With a focused team, breakthrough performance doesn't require breakthrough compute. Focus on the things that matter, and join the team. As a Member of Technical Staff with a focus on Multimodal AI, you will: Design and develop cutting-edge multimodal AI systems, integrating various modalities such as text,
Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friend
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us—that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale—from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Nuro's autonomous vehicle platform has to work - not just in the easy cases, but in the hard ones. The ones we design for, simulate at scale, and deliberately break to understand. We're looking for a Senior/Staff Systems Engineering TPM who owns the technical substance of how we validate autonomy: what we test, why we test it, and whether our coverage actually means something. This is not a planning or scheduling role. You'll work embedded with Autonomy, Simulation, and Systems Engineering teams to drive the technical rigor behind our validation program — defining scene sets, structuring fault injection campaigns, and ensuring our simulation coverage is meaningful, traceable, and systematically growing. The program infrastructure is owned elsewhere; your job is to make sure what's inside it is technically sound. About the Work Scenario & Coverage Strategy Understanding the taxonomy of challenging scene sets used for auto
Electrical Wiring Installation Technical Designer (Senior and Lead) — 2 Locations. Apply via Workday.
SoC Physical Design Engineer, Senior Member of Technical Staff (SMTS) — 2 Locations. Apply via Workday.
SoC Architecture and Design Engineer, Senior Member of Technical Staff (SMTS) — 2 Locations. Apply via Workday.
About the Team OpenAI Finance helps ensure the organization is set up for success in pursuit of its mission of ensuring that artificial general intelligence benefits all of humanity. Within Finance, the Technical Revenue team partners with Product, Legal, GTM, Strategic Finance, Revenue Accounting, Finance Systems, and the company’s GTM Deal Desk organization to enable scalable, audit-ready monetization. We advise on commercial and contract design, establish defensible accounting positions under ASC 606, and provide clear conclusions and handoffs for downstream execution by Revenue Accounting Operations. About the Role We’re looking for a Senior Manager of Technical Revenue Enablement to lead Revenue Recognition deal advisory for OpenAI’s general B2B commercial activity. Reporting to the Head of Technical Revenue, you will serve as the primary Revenue Recognition counterpart to OpenAI’s Deal Desk organization, partnering with Legal, GTM, Product, Pricing, and Strategic Finance throughout the presignature deal lifecycle. You will own intake and triage, advise on non-standard terms, approve arrangements supported by established policy and precedent, and route novel or strategic matters to the appropriate technical owner. You will build a scalable deal-advisory model by translating ASC 606 into practical contract guardrails, approved language, decision trees, review thresholds, and clear service levels. This role requires deep technical accounting judgment, commercial fluency, strong stakeholder influence, and the ability to make timely, risk-based decisions in a fast-moving environment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead the Revenue Recognition deal-advisory function for general B2B transactions, serving as the primary finance counterpart to OpenAI’s GTM Deal Desk organization. Partner early with GTM Deal Desk, Legal, GTM, Pr
Senior FM with Technical / Admin background Address: Plot 3 Jigani Link Road Bommasandra Industrial Area Bangalore Facility: CARL ZEISS - BANGALORE - IFM SERVICES Qualification: Graduate Experience: 25 - 15 years Source: Sodexo India | Job Code: IJP575324
The observability market is shifting from surfacing data to delivering answers. MongoDB is looking for a Staff Product Manager to lead that shift for database users, owning the strategy that takes customers from raw telemetry to AI-powered diagnostics and autonomous remediation, so developers can focus on building great applications instead of managing infrastructure. You will define how MongoDB turns raw telemetry into actionable intelligence, set the vision for AI-powered root cause analysis and proactive recommendations, and shape what best-in-class database observability looks like at global scale. The ideal candidate has experience shipping products that deal with data at scale, can engage deeply with senior engineering on technical architecture, and knows how to balance long-term platform investment against near-term customer value. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What you'll do Define the vision, strategy, and multi-year roadmap for MongoDB observability, balancing the needs of developers, ops teams, enterprise customers, and internal engineering teams Help shape the next generation of AI-powered and agentic observability, including intelligent anomaly detection, automated root cause analysis, and proactive recommendations that help customers resolve issues before they escalate Own product strategy for experiences that span database health, performance diagnostics, alerting, log analysis, and data visualization, creating a coherent observability journey rather than a collection of disconnected tools Identify high-impact opportunities across the observability stack, from how customers monitor and understand their deployments to how MongoDB can reduce the operational burden of managing a database fleet at scale Lead customer discovery with developers, DBAs, and enterprise teams; turn qualitative and quantitative insights into clear product decisions that reduce time spent managing the database and incr
The Security Libraries team owns the customer-side integrations behind Datadog’s run-time security products — App & API Protection , Workload Protection , and Code Security — shipping and maintaining security capabilities across seven open-source language libraries ( .NET , Java , Go , Node.js , Python , Ruby , PHP ) and a set of HTTP proxy integrations (Envoy, NGINX, and HAProxy), running inside thousands of production clusters worldwide. Recent work spans exploit prevention (RASP), WAF detections, API Security, code security (IAST and SCA), and AI-assisted onboarding. As Engineering Manager, you’ll lead part of this polyglot team, setting the technical bar and team culture while driving the pace at which new detections and AI-assisted capabilities reach customers. This is a hands-on role: you’ll balance people leadership, product and roadmap ownership, and the operational health of code that runs in production at massive scale, with room to grow into more of Datadog’s security portfolio over time. 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: Lead, grow, and develop a team of roughly 4-8 library engineers — coaching, giving direct feedback, and empowering senior ICs as technical leaders Own team delivery and productivity: planning, milestones, reviews, and the on-call rotation Set product direction with Product Management and balance priorities across App & API Protection, Workload Protection, and Code Security Stay technically close to the work — apply strong technical judgment, contribute code where it matters most, and keep quality and architecture high Build strong relationships and drive alignment across the language teams and product, backend, and frontend partners Shape team identity and culture, and own accountability when problems oc
At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Vanta's App Primitives team owns the shared building blocks that span data structures to UI: comments, notifications, event logs, feature flags, and task management. We own the general infrastructure; product teams own the logic built on top. Getting this layer right unlocks velocity for every team at Vanta. As the Engineering Manager, App Primitives at Vanta, you'll lead the team building the shared product primitives that every Vanta product team depends on, owning the infrastructure layer that makes collaboration, communication, and core workflows possible across the entire platform. Our Engineering Managers develop and grow high-performing teams that deliver significant value to our customers and enable our business to scale. This role sits at the intersection of technical architecture and team development, with real authority to set direction and grow a world-class platform team. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an Engineering Manager at Vanta: Lead and grow the App Primitives team, owning hiring, team health, delivery, and the development of senior engineers and technical leads Own the strategy and roadmap for Vanta's shared product primitives: comments infrastructure, notifications platform, event log, feature flag system (Statsig), and task management Define and steward the interface model between App Primitives systems and product teams, ensuring product teams can build on top of shared infrastructure quickly and safely, without owning the underlying systems themselves Partner closely with product engineering leaders across Vanta to surface developer ne
At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Vanta's App Primitives team owns the shared building blocks that span data structures to UI: comments, notifications, event logs, feature flags, and task management. We own the general infrastructure; product teams own the logic built on top. Getting this layer right unlocks velocity for every team at Vanta. As the Engineering Manager, App Primitives at Vanta, you'll lead the team building the shared product primitives that every Vanta product team depends on, owning the infrastructure layer that makes collaboration, communication, and core workflows possible across the entire platform. Our Engineering Managers develop and grow high-performing teams that deliver significant value to our customers and enable our business to scale. This role sits at the intersection of technical architecture and team development, with real authority to set direction and grow a world-class platform team. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an Engineering Manager at Vanta: Lead and grow the App Primitives team, owning hiring, team health, delivery, and the development of senior engineers and technical leads Own the strategy and roadmap for Vanta's shared product primitives: comments infrastructure, notifications platform, event log, feature flag system (Statsig), and task management Define and steward the interface model between App Primitives systems and product teams, ensuring product teams can build on top of shared infrastructure quickly and safely, without owning the underlying systems themselves Partner closely with product engineering leaders across Vanta to surface developer ne
Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Ship state of the art models to production. Design and implement novel research ideas. Build elegant training/deployment pipelines. Join us at a pivotal moment, shape what we build and wear multiple hats as an intern! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term. As a Machine Learning Intern, you will: Design, train and improve upon cutting-edge models. Help us develop new techniques to train and serve models safer, better, and faster. Train extremely large-scale models on massive datasets. Explore continual and active learning strategies for streaming data. Learn from experienced senior machine learning technical staff. Work c
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