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About the Team: Tubi's Internal Tools team is at the forefront of AI integration, developing everything from developer resources to production-grade AI for business operations. We are the group responsible for turning AI from an experiment into an operating capability: training, infrastructure, developer agents, and AI-powered business systems. Engineers operate with high ownership and autonomy, collaborating on shared architectural decisions and AI infrastructure. What You'll Do: Own systems end to end — design them, build them, and support them in production. Lead the projects you own: sequence the work, decide what lands first, and set technical direction for the engineers working with you. Sit with the people who use what you build, and turn what you learn there into a system. Design the service boundaries, contracts and schema evolution that let our platforms grow without breaking the teams depending on them. Make our AI systems dependable in production: evaluation harnesses, human approval steps before an agent acts, retries that handle a model returning something unexpected, and cost tracking that tells you what a task costs before you run it. Build what other engineers build on — agent skills, tool and MCP integrations, shared libraries — and raise the bar through code review, design discussion and mentoring. Spot the platform work nobody has asked for yet, make the case for it, and build it. Your Background: 5+ years of professional experience building and operating production systems, from design through production ownership. A system you designed and can walk us through end to end — where its boundaries sit, what constrained it, and what you chose against. Strong programming proficiency in a statically typed language such as Rust, Go, C++, Java, Kotlin, C#, or TypeScript. Production Rust is a plus rather than a requirement. You have owned a service in production: you wrote the runbooks, you knew what it cost, and you were the one paged when it broke. Expe

About the team The ChatGPT Library team is building the persistence layer that helps people and organizations collaborate with increasingly capable AI systems. ChatGPT Library provides users with a durable place for their files, context, and creations, forming a substrate between humans and agents—a foundation for AI that can remember, retrieve, and act on the right context over time. The team sits within the Personalization organization and partners closely with product, design, research, model, and infrastructure teams. Its work helps models become a useful second brain for individuals—for example, answering questions such as “What did I work on last week?”—and supports enterprise use cases that turn company knowledge into accessible, actionable context. About the role We are looking for a hands-on engineering manager to lead a team of approximately 9–10 engineers and own execution across the product roadmap. This is a technical leadership role for someone who can set a high product bar, build a strong team, shape architecture, and contribute directly when needed. You will form and translate an ambitious product vision into a focused roadmap and help the team ship reliable, intuitive experiences at the intersection of AI, knowledge, and collaboration. The ideal candidate leads by example. You are comfortable moving between people leadership, product decisions, technical design, and code. Founder or early-stage startup experience is especially valuable because the role requires urgency, sound judgment under ambiguity, and a willingness to operate across boundaries. In this role you will • Lead, coach, and grow a team of approximately 9–10 engineers while creating clarity, accountability, and a healthy execution rhythm. • Own the engineering roadmap for Library, working with product and design partners to prioritize the highest-impact problems. • Set a high bar for product quality, technical excellence, reliability, privacy, and user trust. • Provide hands-on techni

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As the Engineering Manager for the FlashArray (FA) Foundation Quality Engineering team, you will build and lead a high-performing team of Quality Engineers and Software Test Developers in Bangalore. You will combine people leadership, technical judgment, and execution discipline to drive the quality, test automation, and release readiness of foundational FlashArray capabilities. Working at the intersection of software, hardware, firmware, and cloud infrastructure, you will partner closely with Development, Product Management, Release, and Support teams. Your focus will be translating complex roadmap requirements into modern test strategies, establishing strong shift-left CI/CD signals, and ensuring our products consistently deliver industry-leading reliability to our customers. WHAT YOU’LL DO Build & Lead a High-Performing Team: Hire, mentor, and coach a newly forming team of quality and automation engineers in Bangalore, fostering a culture of technical excellence, continuous learning, and shared ownership. Drive Quality Strategy & Shift-Left Automation: Define and execute the FA Foundation quality roadmap—including risk-based coverage, automated CI/CD pipeline integration, fault injection, and release-readiness criteria across software, firmware, and hardware. Partner Cross-Functionally for Delivery: Collaborate early in the design cycle with Development, Architecture, Product, and Release teams to impro

Machine Learning Engineer We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: Multiple years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native:

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

AI Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI- powered innovations to enhance search relevance and ITSM workflows. What You Will Do: Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customerʼs data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 3-5 years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals who ask for payments in exchange for interviews or offer letter

Staff Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI-powered innovations to enhance search relevance and ITSM workflows. What You Will Do Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customer’s data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries. Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 5+ years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals wh

Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We are seeking a Software Engineer for our team in Gurgaon. Our Core Technology team has some of the best programmers in India working on cutting edge technologies to build a super fast and robust trading infrastructure handling millions of dollars worth of trading transactions every day. Requirements Contribute to all layers of backend systems including databases, APIs and applications Design, build and maintain applications for business requirements Architect scalable and reliable applications Write clean and modular code, following good coding standards and practices Troubleshoot and debug applications Be involved in the entire application lifecycle Collaborate with multidisciplinary team of front-end developers, engineers and system administrators Devise innovative solutions to address new and complicated challenges Build reusable code and libraries for future use Take lead on projects, as needed Work in a high paced competitive environment Qualifications The ideal candidate will have: Engineering degree in Computer Science (preferred) or any other discipline from a Tier 1 college. 3 to 4 years of relevant experience in designing and improving information systems Proficiency in Python programming Extensive experience working with relational databases and handling large datasets Good Understanding of object oriented and asynchronous programming Familiarity with front-end languages such as HTML, JavaScript and CSS Knowledge of Linux systems and bash scripting Good communication and interpersonal skills Willingness to continuously learn and improve Ability to work in fast paced environment under pressure and manage multiple high priority projects Good to have: Experience in Financial services space/domain Experience in and understanding of system design decisions Experience in leading small teams or projects Benefits: Our open and casua

A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What you'll do Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance. Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions. Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products. Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications. Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business. Ensure compliance with industry standards and best practices in AI/ML. What's required Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems. Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven en

Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production

Role Overview You’ll be the Principal Software Engineer driving the next generation of a large-scale enterprise SaaS platform. In this role, you combine deep hands-on engineering with high-impact technical leadership, shaping how cloud-native and AI-enabled products are designed and built. You’ll design and deliver secure, scalable, serverless systems on AWS using TypeScript and Node.js, modernize critical platform components, and set the technical direction for multiple teams. You’ll also lead how AI capabilities are integrated across the product ecosystem, ensuring they are transparent, observable, and compliant. If you enjoy system-level thinking, complex distributed architectures, and mentoring senior engineers while still staying close to the code, this role gives you company-wide impact and the opportunity to define the long-term technical vision. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and delivery of secure, scalable, serverless applications on AWS using TypeScript/Node.js. Define and evolve the platform architecture, driving modernization, performance, resilience, and maintainability. Design and operate distributed, event-driven systems using services like Lambda, DynamoDB, Aurora, S3, and EventBridge. Shape and implement AI-enabled solutions, embedding governance, observability, and responsible AI practices into the platform. Own Infrastructure as Code (e.g., Terraform, AWS CDK, CloudFormation) to reliably provision and manage cloud infrastructure. Mentor senior engineers, influence technical decisions across teams, and clearly communicate complex concepts to diverse stakeholders. These are the essentials you’ll need to get an interview Extensive experience (typically 12+ years) building secure, production-grade software systems. Proven track record architecting and delivering cloud-native, serverless applications on AWS. Strong expertise in Node.js, TypeScript, REST API design, and at leas

You’ll shape the future of a business‑critical platform as the technical lead across both product engineering and cloud infrastructure. You’ll modernize a mature .NET application running on AWS today, while steering its evolution toward a cloud‑native, React/Node.js, AI‑enabled architecture. If you enjoy owning architecture end‑to‑end, from backend and frontend through CI/CD, DevOps, and AWS infrastructure, this role gives you real influence at Staff Engineer level and the opportunity to set engineering standards that others follow. You’ll spend your time leading complex .NET and React features, designing scalable AWS infrastructure with Infrastructure as Code, and building automation that makes releases fast, safe, and repeatable. You’ll work on performance, reliability, and modernization in equal measure—fixing what’s slowing the platform down today and designing what it will look like in the next generation. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and development of enterprise .NET services and APIs that power a business‑critical platform. Design and operate AWS infrastructure (using AWS CDK in TypeScript) to support secure, scalable, multi‑environment deployments. Build and optimize CI/CD pipelines (AWS CodePipeline, CodeBuild, Windows build agents) to make shipping .NET and React changes fast and reliable. Drive modernization initiatives across the stack, including clean architecture, refactoring legacy components, and reducing technical debt. Design and tune PostgreSQL and MSSQL database solutions for performance, scalability, and reliability. Mentor engineers and influence engineering practices across teams, raising the bar on cloud, DevOps, and software design. These are the essentials you’ll need to get an interview Significant experience (typically 8+ years) delivering and operating scalable enterprise software, owning both application code and cloud infrastructure. Deep hands‑on expertise with C

About the Role: We are looking for a Senior DevOps Engineer to join our DevOps team at K Health. You will own and evolve the infrastructure underpinning a healthcare AI platform serving patients and enterprise health system partners. This is a high-ownership role: you will architect and operate cloud environments across K Health and its enterprise partners, lead complex infrastructure migrations, drive disaster recovery programs, and help build the next generation of AI-powered operations tooling. You will also mentor junior engineers and collaborate closely with product and engineering teams across the company. This is a hybrid role based in New York City (4 days/week in office) and includes participation in a daytime on-call rotation. What you will do: Own the design, implementation, and evolution of our GKE-based Kubernetes infrastructure across K Health and enterprise partner environments. Build and maintain our Terraform modular infrastructure library, including reusable modules with automated testing, across GCP, Cloudflare, and AWS. Architect, build, and maintain GitLab CI/CD shared pipeline templates used by all engineering teams (build, test, security scanning, deployment). Own and maintain self-hosted infrastructure software running in-cluster, including GitLab, ArgoCD, Langfuse, DependencyTrack, NGINX Ingress, and others. Implement and support security and compliance controls across infrastructure and the software supply chain - secrets management, pipeline secret detection, container scanning, SOC2 and HIPAA. Drive disaster recovery readiness: design failover scenarios, author runbooks, and lead periodic DR tests. Lead development of AI-powered operations tooling and agentic infrastructure. Monitor, troubleshoot, and improve production system reliability; respond to incidents during on-call shifts. Mentor junior DevOps engineers and establish team-wide engineering standards. What we are looking for: 5+ years of experience in DevOps, platform engineering,

About the Team The Merchant (Mx) AI/ML team is a cornerstone of DoorDash’s merchant organization. We empower our restaurant partners to thrive on DoorDash by building intelligent, scalable AI systems that simplify operations, elevate their digital presence, and enhance customer engagement. Our world-class machine learning engineers develop production-grade AI solutions that power the entire merchant lifecycle — from onboarding and store setup to menu management, growth, and real-time order operations. The team is deeply customer-obsessed and impact-driven, focused on turning cutting-edge research in LLMs, multimodal learning, generative AI, and agentic automation into products that make our merchants more successful every day. About the Role We’re looking for an Engineering Manager to lead the Mx AI/ML team, driving the design and deployment of next-generation AI product solutions that power our merchant experiences. This is a highly cross-functional leadership role — you’ll collaborate with product, design, operations, and data science teams to define the AI roadmap, guide technical direction, and deliver end-to-end AI/ML solutions at massive scale. You’ll lead a team of talented ML engineers who are building real AI products delivered to merchants’ fingertips, helping them become more successful on DoorDash. You’re excited about this opportunity because you will… Lead and grow a team of exceptional AI/ML engineers developing production-grade machine learning and generative AI solutions for the merchant ecosystem. Define a multi-year strategy and execute the AI roadmap across key Mx pillars — Onboarding, Menu Media Understanding & Generation, Menu Metadata Intelligence, and Agentic Task Automation. Partner with product and operations to translate merchant pain points into scalable AI-powered solutions. Own the end-to-end lifecycle of ML systems — from ideation and experimentation to productionization and continuous improvement. Drive innovation in multimodal AI