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we are looking for a MLOps Engineer.
As an MLOps Engineer, you will work at the intersection of backend engineering and machine learning, building the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features used by hundreds of thousands of families.
What you'll be doing -
Build Production AI Systems - Design and implement backend services and end-to-end AI solutions that integrate Deep Learning models, Computer Vision algorithms, and GenAI into real features.
Power Experimentation and Validation - Contribute to the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Develop Data Pipelines - Build and maintain scalable data pipelines and big-data solutions that feed AI capabilities reliably and with an eye on cost and scale.
Own What You Ship - Take features end-to-end within your squad, from planning and design through implementation, deployment, and monitoring in production.
Cross-functional Collaboration - Work closely with the Algorithms and Data teams to tackle complex, real-world problems, helping translate research into shippable, maintainable systems.
Backend Guild Engagement - Actively contribute to a backend guild that drives Software Engineering and System Design best practices, guidelines, and standards across the R&D team.

We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

we are looking for a MLOps Team Lead.
As an MLOps Team Leader , you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.
What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.
Who You Are:

We are looking for a highly skilled and versatile Senior Backend Engineer to join our development team. As a Senior Backend Engineer, you will be responsible for designing, developing, and maintaining the backend infrastructure and components of our platform. As part of your role, you will also work on the frontend aspects of our platform and collaborate with stakeholders and cross-functional teams to optimize full-cycle system performance
Responsibilities:
Design, develop, and maintain backend systems and APIs to support our web applications.
Implement and optimize data storage solutions, including databases, to ensure efficient and reliable data management.
work closely with front-end developers to integrate backend functionalities and ensure a seamless user experience.
Collaborate with product managers, stakeholders, and cross-functional teams to gather requirements, translate them into technical specifications, troubleshoot and resolve backend-related issues, and optimize system performance.

Were looking for an AI Software Engineer to own the RL Gym platform end-to-end: from architecting multi-site web environments that simulate real-world attack surfaces, to optimizing our in-house orchestration harness (AgenticVerse) for high-performance delivery into customer training pipelines.
This is a builder role. Youll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. Youll interact directly with customer engineering teams to understand their infrastructure constraints and deliver environments that meet their scale and reliability requirements.
Why this role
This is one of the few roles in the industry where your code directly influences how the next generation of AI models are trained. Youll be at the center of advancing AI safety, building systems that the worlds top labs depend on to make their models more robust. The work is technically deep, the problem space is genuinely novel, and the field is moving faster than any team can keep up with alone. Theres no playbook. Youll write it.
What youll do:
Platform & performance
Own and evolve AgenticVerse, our in-house orchestration harness that provisions and manages RL environments at scale. Focus on performance: low-latency provisioning, high concurrency, minimal overhead per environment instance
Design and build isolated, reproducible web environments using Firecracker microVMs or Docker containers
Architect multi-site scenarios (3-4 interconnected web applications per task) with rich interactions: drag-and-drop, file uploads, authentication flows, LLM-in-the-loop components
Implement deterministic verifiers that evaluate agent behavior with zero ambiguity
Customer delivery
Work directly with engineering teams at leading AI labs to integrate RL Gym environments into their training and evaluation pipelines
Translate customer specs into working environments, iterating rapidly on feedback
Own the technical relationship: SLAs, API contracts, integration architecture
Adapt environment delivery formats to cus tomer infrastructure (real-time API calls vs. offline batch, managed vs. raw artifacts)
Build customer-facing UIs when needed (dashboards, environment configuration portals, monitoring interfaces)
Rapid prototyping
Take ambiguous problem descriptions and produce working prototypes within days, not weeks
Validate new environment types, interaction patterns, and verifier approaches quickly
Build internal tooling that accelerates scenario authoring and testing.

We're looking for an experienced hands-on Software Engineering Team Lead to lead a highly skilled team of backend and frontend engineers through implementation, delivery, iteration, and build scalable systems that serve our customers.

Responsibilities:
Foster a positive, collaborative culture and grow the teams capabilities.
Lead and mentor engineers to ensure on-time delivery, quality development, productivity, and efficiency by conducting and lead design reviews & code reviews.
Work together with product managers to translate requirements into scalable technical solutions.
Balance refactoring and evolution with steady delivery of new features.
Drive a culture of technical excellence, ownership, and continuous improvement.
Oversee system reliability, monitoring, performance optimization and incident response.

As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.

If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!

Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

We are looking for a highly skilled and versatile Backend Engineer to join our development team. As a Backend Developer, you will be responsible for designing, developing, and maintaining the infrastructure and components of our platform. As part of your role, you will work on the backend aspects of our platform and collaborate with stakeholders and cross-functional teams to optimize full-cycle system performance.
Responsibilities:
Develop and maintain code deployed on the cloud side and on Linux.
Collaborate with cross-functional teams to achieve project goals.
Implement high-performance applications with high coverage, maintaining minimal footprint ensuring code is maintainable.
Troubleshoot and resolve complex technical issues related to Linux internals.

We are seeking engineers with hands-on experience in developing and managing distributed systems and microservices in a production environment. The ideal candidate should have a solid background in infrastructure and operations.
The team builds high-throughput ingestion and processing pipelines, efficient storage on object stores, and systems for data governance, usage reporting, and routing data to multiple physical locations.
You will work on cloud-native, production systems written in Rust and Scala, operating at scale with Kafka, Postgres, Redis, and object storage, run on Kubernetes and operate in a multi-cloud environment.
Responsibilities:
Develop and operate distributed systems in production
Build Kafka-based ingestion and processing pipelines
Design systems for data governance, retention, deletion, and usage reporting
Work with Postgres and Redis, requiring solid database design and operational knowledge
Implement efficient persistence using column-oriented data formats and object storage.