Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.
\nEA SPORTS is one of the leading sports entertainment brands in the world, with top-selling videogame franchises, award-winning interactive technology, fan programs, and cross-platform digital experiences.
\nAs one of the largest sports entertainment platforms in the world, EA SPORTS FC is redefining football with genre-leading interactive experiences, connecting a global community of fans to The World's Game through innovation and unrivaled authenticity.
\nWith more opportunity than ever to design, innovate and create new, immersive experiences that bring joy, inclusivity, and connection to fans everywhere, we invite you to join our passionate and dynamic team as we pioneer the future of football fandom.
\nSenior Full Stack Engineers are key drivers behind the technology that powers our games and the experiences millions of players love. In this role, you’ll design and build scalable backend services, data pipelines, and APIs that move and process massive amounts of real-time game data. As part of the Gameplay Advance team at EA, you’ll work alongside world-class engineers to push gameplay technology forward,solving complex technical challenges, influencing architecture, and helping shape the future of how our games are built and played.
\nYour Responsibilities:
\nYour Qualifications:
\nPlease note that you do not need to qualify for all requirements to be considered. We encourage you to apply if you can meet most of the requirements and are comfortable opening a dialog to be considered.
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\nWe’re looking for an experienced Site Reliability Engineer (SRE) to join our infrastructure team. In this role, you’ll blend software engineering and systems engineering to keep our large-scale distributed AI infrastructure reliable and efficient. You’ll work closely with ML researchers, data engineers, and product developers to design and operate the platforms that power training, fine-tuning, and serving generative AI models.
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\nCollaboration: Partner with ML engineers and platform teams to improve developer experience and accelerate research-to-production workflows.
\nQualifications:
\nRequired Qualifications: 4+ years of experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering roles.
\nPreferred Qualifications: Strong proficiency in Kubernetes, Docker, and container orchestration. Knowledge of CI/CD pipelines for Inference and ML model deployment. Hands-on experience with public cloud platforms like Azure/AWS/GCP and infrastructure-as-code. Expertise in monitoring & observability tools (Grafana, Datadog, OpenTelemetry, etc.). Strong programming/scripting skills in Python, Go, or Bash. Solid knowledge of distributed systems, networking, and storage. Experience running large-scale GPU clusters for ML/AI workloads (preferred). Familiarity with ML training/inference pipelines. Experience with high-performance computing (HPC) and workload schedulers (Kubernetes operators). Background in capacity planning & cost optimization for GPU-heavy environments.
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\nCollaboration: Partner with ML engineers and platform teams to improve developer experience and accelerate research-to-production workflows.
\nQualifications:
\nRequired Qualifications:
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\nKnowledge of CI/CD pipelines for Inference and ML model deployment.
\nHands-on experience with public cloud platforms like Azure/AWS/GCP and infrastructure-as-code.
\nExpertise in monitoring & observability tools (Grafana, Datadog, OpenTelemetry, etc.).
\nStrong programming/scripting skills in Python, Go, or Bash.
\nSolid knowledge of distributed systems, networking, and storage.
\nExperience running large-scale GPU clusters for ML/AI workloads (preferred).
\nFamiliarity with ML training/inference pipelines.
\nExperience with high-performance computing (HPC) and workload schedulers (Kubernetes operators).
\nBackground in capacity planning & cost optimization for GPU-heavy environments.
\nWork on cutting-edge infrastructure that powers the future of Generative AI.
\nCollaborate with world-class researchers and engineers.
\nImpact millions of users through reliable and responsible AI deployments.
\nCompetitive compensation, equity options, and comprehensive benefits.
\nSoftware Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.
\nSoftware Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
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\nAt Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment.
\nAs a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.
\nImpact and Responsibilities:
\nIdeally you’d have:
\nNice to haves:
\nCompensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.
\nFor pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $252,000-$315,000 USD
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\nYou will drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. You'll collaborate with cross-functional teams to define, design, and deliver new features. You'll also proactively identify opportunities for, and drive improvements to, current programming practices, including process enhancements and tool upgrades.
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\nNice to haves include experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt). Experience with authentication/authorization systems (Zanzibar, Authz, etc.) is also a plus. Experience scaling products at hyper-growth startups is highly valued. Excitement to work with AI technologies is a must.
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\nWe aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement.
\nAs a Solutions Architect in the UAE Pre-Sales team, you will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges.
\nYou'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customised solutions to help our customers achieve their goals and guide their businesses forward.
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\nMicrosoft AI are looking for a talented Member of Technical Staff, HPC Operations Engineering Manager to join their MAI SuperIntelligence Team. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising haptic entertainment technology. You'll work directly with leadership to shape the company's direction in the cinema and simulation markets.
\nAbout the Role
\nIn this role, you'll lead a team of Site Reliability Engineers who blend software engineering and systems engineering to keep our large-scale distributed AI infrastructure reliable and efficient. You'll work closely with ML researchers, data engineers, and product developers to design and operate the platforms that power training, fine-tuning, and serving generative AI models.
\nAccountabilities
\nThe Candidate we're looking for
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\nBenefits
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