Responsible for executing the HR&IR strategy and initiatives for building a high performing, motivated and engaged workforce at the cluster. Creating a dynamic, inclusive and high-performance stimulating work environment for cluster employees through effective HR processes & policies, talent acquisition, learning 8 development, talent management, employee engagement & HR operations. Create value addition for business and competitor differentiation through innovative use of people dimension and proactive IR approach.. Implement the industrial relations strategy effectively to establish cordial labour relations, employee relations, and training in the support of organization's labour relations strategy at the Cluster level. Ensuring statutory compliance at the cluster level as well as resolving issues related to trade union relations and labour laws. Source: Adani Group | Job ID: 54543
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The Zonal Lead - Security-Tx is responsible for managing security operations across the cluster in alignment with business objectives and the Security Strategy Roadmap. This includes safeguarding infrastructure to ensure business continuity, fostering a secure environment for employees and stakeholders, and enhancing the security of designated protected. The role oversees fraud and misconduct prevention through a structured framework for detection, response, and continuous improvement. By conducting detailed security risk assessments, the Security Lead identifies, mitigates, and eliminates potential threats while ensuring the protection of tangible and intangible assets within the cluster. Source: Adani Group | Job ID: 55870
The Lead - Cluster CRM is responsible for managing all post-sales customer interactions and ensuring a seamless customer experience for assigned sites. This role oversees end-to-end customer relationship management, including sales documentation, collections, and issue resolution, from the booking stage through to customer handover. The Lead plays a crucial role in maintaining customer satisfaction and ensuring operational efficiency across all CRM processes. Source: Adani Group | Job ID: 55576
At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's need to detect and respond to security events across its production and corporate environments is growing as the company scales. We're looking for a Senior Detection and Response Engineer to own detection engineering and to lead incident response when it counts, coordinating the response and driving it to resolution. This is a high-ownership role with real room to shape how detection and response works at Anyscale. You will own the detection pipeline, the response runbooks, and incident response, reporting to the Head of Security and partnering with engineering. This role is based in India. In your first year, success looks like strong detection coverage across our cloud, endpoint, and runtime telemetry, a working correlation and alerting pipeline, and incident response runbooks that have been exercised in practice. What You'll Do Own and build detection coverage across cloud, endpoint, and runtime telemetry. Own a centralized correlation and alerting capability that turns telemetry into actionable detections. Own incident response: runbooks, escalation paths, and coordination during an incident, across corporate and production environments. Drive detection of anomalous activity across the environments
Senior Cloud Security Engineer At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's security needs are growing as we operate more production and cloud infrastructure for larger and more demanding customers. We're looking for a Senior Cloud Security Engineer to own the security of that infrastructure. This is a hands-on, high-ownership role: you will own how our production and cloud environments are hardened, isolated, and monitored. You will set and drive the direction for infrastructure and production security, reporting to the Head of Security and partnering closely with the wider engineering organization. This role is based in the San Francisco, Bay Area. In your first year, success looks like hardened and well-segmented production environments, strong runtime security coverage across our container footprint, and a clear, defensible story for how we secure the infrastructure our customers rely on. What You'll Do Own the security posture of Anyscale's production and cloud infrastructure across AWS and Azure, including hardening, network segmentation, and tenant isolation. Own runtime security coverage across our Kubernetes environments, from deployment through detection of anomalous activity. Partner with engineering on secure infrastructure architectur
At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's product security needs are growing as we ship to larger and more demanding customers. We're looking for a Senior Product Security Engineer to own our secure software development lifecycle and to be engineering's partner on building security into the product. Reporting to the Head of Security, you will work in close partnership with engineering. This is a senior, high-ownership role. You will own and operate a scalable SSDL, partner with engineering on security features and secure design, review the security of existing systems and new initiatives, and own how we find, track, drive to resolution and report on vulnerabilities in what we ship. This role is based in India. In your first year, success looks like an SSDL that scales with engineering rather than gating it, security review embedded in how new initiatives ship, and accurate, on-demand vulnerability reporting backed by a working path to resolution. What You'll Do Own and operate a scalable secure software development lifecycle: threat modeling, security requirements, secure design practices, and scanning that engineering can readily adopt. Partner with engineering on security features and secure-by-design architecture, from early design through i
At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's security and compliance needs are growing as we work with larger and more demanding customers. Compliance is increasingly a customer-facing, contractual function rather than an internal exercise, and we are looking for someone to own it. This role owns that function end to end: our audits, our evidence base, our risk register, and the security diligence that customers put us through before and during a contract. You will work directly with the Head of Security and across engineering, IT, legal, and sales. This is a program-ownership role with the autonomy and accountability that implies. You will not have a senior compliance function above you to defer to; you are that function. In your first year, success looks like a complete and defensible evidence base with clean audit outcomes, a repeatable way to answer customer security diligence, and a risk register that leadership actually uses. What You'll Do Own our SOC 2 Type II and ISO 27001 programs, and future frameworks as we take them on, including scope, evidence, control operation, and the relationship with our external auditors. Own and complete the control evidence base in our compliance automation platform, moving controls from partially substantia
At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale runs on a small, high-leverage IT function, and we're looking for an IT Engineer to own it. This is a hands-on engineering role, not a help desk or tier-1 support role. Roughly half the job is software: you will own and extend a set of internal automation and notification services wired into our directory and hardware systems. You should be comfortable owning a codebase and a GitHub repository, not only vendor admin consoles. The other half is the identity, endpoint, hardware, and vendor backbone that keeps a company of roughly 200 people, close to half of them engineers, productive across three public clouds. Reporting to the Head of Security and IT, you will work closely with security, engineering, and the people team. This role is based in the San Francisco Bay Area on a hybrid schedule. What You'll Do Own identity and access: Okta and Google Workspace administration, group-based authorization, 1Password Enterprise, passkeys, and automation driven provisioning and deprovisioning. Own and extend our internal automation services, and run them on scoped service accounts with sound security and hygiene. Own the endpoint fleet through mobile device management, including device trust posture checks, endpoint
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? The Data Infrastructure team at Cohere is responsible for the storage and data movement layer underlying every model training run. We're building the unified storage layer that feeds our training workloads. It needs to serve petabytes of training data and model checkpoints fast enough to keep thousands of GPUs busy across several training clusters. In this role, you’d have an opportunity to build this system from the ground up. You’d be a key contributor, working on a problem few teams have had to solve at this scale. In this role, you will: Design, build, and operate the distributed storage system that feeds model training and evaluation. Run this system multiple on Kubernetes clusters at petabyte scale. Work with researchers and training-infra teams on how jobs actually read and write data, and turn that into throughput, latency, and durability requirements Work through the networking, I/O, and consistency problems of moving large datasets and checkpoints across regions and backends, with GPU idle time and time-to-insight as the measures of success You may be a good fit if you have: Strong storage fundamentals,
The Architect is responsible for the architectural design and coordination across multiple projects within the cluster. The role ensures that design, construction, and marketing objectives are met through effective communication, design reviews, and coordination with various teams, including MEP, sales, and external consultants. This position plays a crucial role in the day-to-day management of architectural activities, contributing to project execution, quality assurance, and alignment with business goals. Source: Adani Group | Job ID: 54488
The Architect is responsible for the architectural design and coordination across multiple projects within the cluster. The role ensures that design, construction, and marketing objectives are met through effective communication, design reviews, and coordination with various teams, including MEP, sales, and external consultants. This position plays a crucial role in the day-to-day management of architectural activities, contributing to project execution, quality assurance, and alignment with business goals. Source: Adani Group | Job ID: 41570
About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus
About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte
About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we're building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Anyscale is looking for a Software Engineer to join the ML Developer Experience (MLDevX) team. MLDevX owns the experience layer of the Anyscale platform: the interfaces through which users and coding agents discover, configure, run, observe, debug, and productionize AI workloads. Every user journey crosses this layer through the CLI, SDKs, APIs, UI, Workspaces, MCP, or the workflows and integrations built on top of them. Together, these form the user’s primary interface into Anyscale, turning distributed computing from a systems problem back into a coding problem. We build the common contracts, tools, control-plane services, and architecture that power these surfaces. You will work across the stack from developer tooling to cloud infrastructure and the Ray runtime. Manage long-running operations and make failures across jobs, tasks, actors, nodes, and GPUs easier to diagnose. The systems you build must scale with the platform, remain predictable through failures, and be intuitive for developers, programmable for applications, and operable by coding agents. This is a high impact individual-contributor role with end-to-end ownership. You will work directly with users and field teams to identify high
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will build the model runtime within the inference engine that executes complex, frontier models at scale on OpenAI’s custom silicon. The runtime will sit between models running on the hardware and the upper layers of the cluster serving software stack, translating demanding inference workloads into efficient execution while optimizing for throughput, latency, utilization, and reliability. You will work across model architecture, distributed systems, compilers, kernels, and silicon to design a production-grade runtime comparable in ambition to systems such as vLLM and SGLang, but customized and optimized for OpenAI’s AI accelerator. Your work will shape how new model capabilities map onto the platform and how quickly custom silicon can deliver meaningful performance in production. In this role, you will: Design and implement the LLM inference runtime for frontier models running on custom silicon. Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference. Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization. Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads. Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack. Enable new
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