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Location: London, United Kingdom Workplace: remote We are looking for a Lead Applied Researcher — Pricing to design and evolve dynamic pricing systems for our marketplace. You will develop pricing as a feedback-driven decision system , balancing supply, demand, and business outcomes under uncertainty and delayed signals. Unlike traditional surge-based pricing, our marketplace operates on a unique bid-based pricing model , where prices are shaped through direct negotiation between riders and drivers. This creates a fundamentally different optimization problem, requiring advanced approaches to modeling user behavior, incentives, and marketplace dynamics. Key Responsibilities Design and improve dynamic pricing policies, including elasticity and supply/demand response modeling Frame pricing as a decision system under uncertainty and delayed feedback Develop, test, and deploy real-time pricing algorithms Design and analyze A/B experiments to evaluate pricing impact Productionize models in collaboration with engineering, ensuring scalability and robustness Monitor system performance, including stability, feedback effects, and long-term behavior Contribute to methodological choices (e.g., optimization, control, RL-inspired approaches) Skills, Knowledge and Expertise Professional experience in Data Science, Applied Research, or algorithmic product optimization, preferably in marketplaces or pricing systems Strong background in statistics, optimization, and causal inference Proven ability to move from problem formulation to production-grade solutions Proficiency in Python, SQL, and experience with production ML systems Nice to Have Experience with economic modeling (elasticity, auctions, policy design) Familiarity with control systems, RL, or online optimization Experience working with real-time, high-load systems Why join us Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 47 countries Develop your professional skills with access to mentoring, career consulting, and learning programs Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We are looking for a Lead Applied Researcher — Pricing to design and evolve dynamic pricing systems for our marketplace. You will develop pricing as a feedback-driven decision system , balancing supply, demand, and business outcomes under uncertainty and delayed signals. Unlike traditional surge-based pricing, our marketplace operates on a unique bid-based pricing model , where prices are shaped through direct negotiation between riders and drivers. This creates a fundamentally different optimization problem, requiring advanced approaches to modeling user behavior, incentives, and marketplace dynamics. Key Responsibilities Design and improve dynamic pricing policies, including elasticity and supply/demand response modeling Frame pricing as a decision system under uncertainty and delayed feedback Develop, test, and deploy real-time pricing algorithms Design and analyze A/B experiments to evaluate pricing impact Productionize models in collaboration with engineering, ensuring scalability and robustness Monitor system performance, including stability, feedback effects, and long-term behavior Contribute to methodological choices (e.g., optimization, control, RL-inspired approaches) Skills, Knowledge and Expertise Professional experience in Data Science, Applied Research, or algorithmic product optimization, preferably in marketplaces or pricing systems Strong background in statistics, optimization, and causal inference Proven ability to move from problem formulation to production-grade solutions Proficiency in Python, SQL, and experience with production ML systems Nice to Have Experience with economic modeling (elasticity, auctions, policy design) Familiarity with control systems, RL, or online optimization Experience working with real-time, high-load systems Why join us Help us challenge injustice by creating fair choices for millions of people across in 47 countries Develop your professional skills with access to mentoring, career consulting, and learning programs Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Annual salary from EUR 80 200 gross Final benefits may vary depending on the location.

Location: Hamburg Workplace: Hybrid adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually.   Architecting the sub-millisecond decision engine that powers 200 million daily ad interactions   The Demand Core team and backend platform squads build the foundational infrastructure that determines which of our thousands of active advertising campaigns are relevant to a user the moment they open Playtime. At our scale, system latency is a business failure: downtime means advertisers stop spending, users stop earning rewards, and publisher revenue stalls. As a Staff Backend Developer, you will own the architectural integrity, reliability, and long-term evolution of the distributed systems that power these decisions 200 million times every day across multiple teams. Go microservices load the active ad campaign catalog into memory, evaluating 40+ targeting constraints and 30+ real-time signals like geo, fraud status, budget caps, to rank potential user performance in milliseconds. Beyond individual services, you will define architectural patterns across the entire ad interaction chain: high-throughput processing of clicks, views, MMP postbacks from Adjust and AppsFlyer, and reward-triggering in-app events. You will govern our hybrid messaging architecture using SNS/SQS and Kafka, standardize backend data patterns across DynamoDB, relational, and analytical data stores, and ensure our core ad scoring pipelines remain resilient under massive load.   Your Mission & Who We Are Looking For:   - Production Golang Systems & Architecture Mastery: You bring extensive backend development experience (7+ years, with deep production Go expertise in distributed environments). You will define service boundaries, concurrency models, and runtime optimizations for our +99% Go microservice architecture, scaling the platform reliably beyond hundreds of millions of monthly active users. - High-Throughput Event Streaming & Architecture Patterns: You have deep experience architecting and standardizing asynchronous microservice communication using event backbones like Kafka, SQS/SNS, and Kinesis. You will establish org-wide streaming standards, schema evolution, and CDC patterns to process billions of daily API events and aggregate them into our data lake for sub-second querying. - Large-Scale Data Architecture & Platform Optimization: You understand database internals, distributed storage trade-offs, and low-level web standards. You will standardize data patterns (sharding, replication, DR) across hundreds of terabytes in DynamoDB, MySQL, Druid, and Athena, while leading high-stakes, zero-downtime database migrations and deprecations. - Data Science & Algorithmic Integration at Scale: You quickly grasp complex technical topics, distributed systems trade-offs, and applied mathematics. You will partner with our Data Science team to architect the runtime infrastructure that serves predictive models and machine learning algorithms directly within our sub-millisecond real-time ad targeting engine. - Technical Leadership & Organizational Leverage: You communicate fluently and precisely in spoken and written English. You drive alignment across squads through RFCs and Architecture Decision Records (ADRs), define org-level SLIs/SLOs, sponsor major technical migrations, and mentor Senior engineers across an international engineering team. - Plus: Cloud Resilience & Tooling: Hands-on experience with continuous profiling (e.g., Pyroscope, goroutine dumps), chaos engineering drills, and infrastructure automation using Terraform, Kubernetes, or AWS cloud networking. ‌ 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.   What’s in It for You?   At adjoe, you’re not here to just close JIRA tickets, you’re shaping the architectural foundation behind one of the most impactful platforms in adtech. The systems and patterns you design will reach hundreds of millions of users and power billions of decisions every day.   - Go Big. Own the technical direction and platform architecture with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, establish golden paths that unlock engineering speed, and keep momentum. - Be Direct. Solve complex architectural bottlenecks openly and drive alignment across cross-functional teams. - Thrive Together. Grow with and elevate a diverse, global team of engineers from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, solve hard computer science challenges, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

Location: Shanghai, China Riot Games was established in 2006 by entrepreneurial gamers who believe that player-focused game development can result in great games. In 2009, Riot released its debut title League of Legends to critical and player acclaim. As the most played video game in the world, over 100 million play every month. Players form the foundation of our community and it’s for them that we continue to evolve and improve the League of Legends experience. We’re looking for humble but ambitious, razor-sharp professionals who can teach us a thing or two. We promise to return the favor. Like us, you take play seriously; you’re passionate about games. We embrace those who see things differently, aren’t afraid to experiment, and who have a healthy disregard for constraints. That's where you come in. About the Role As a Senior Technical Artist, Rendering on the Unpublished R&D Product team, you will translate creative direction into scalable, performant real-time rendering solutions. You will work across materials, shaders, lighting, and rendering systems in Unreal Engine 5 (UE5), partnering with engineering, art, and design teams to address visual and technical challenges. You will help improve rendering workflows, establish technical standards, and support consistent visual quality across hardware platforms. You will report into the Tech Lead of the team. Responsibilities: Develop and implement rendering solutions that support visual direction and maintain consistency across platforms. Create, maintain, and optimize UE5 materials, shaders, and related rendering content. Partner with rendering engineers, artists, and designers to deliver rendering solutions within established performance budgets. Define rendering scalability settings, quality tiers, and fallback strategies for different hardware configurations. Profile and optimize shader performance, GPU workloads, memory utilization, and asset loading. Improve rendering workflows, technical standards, production tools, and documentation to support efficient content creation. Provide technical guidance to artists, resolve complex rendering challenges, and promote consistent rendering practices across the team. Qualifications: 5+ years of professional experience in technical art, real-time graphics, or related game development disciplines, including 4+ years working with Unreal Engine. Experience contributing rendering or technical art solutions to a shipped or long-running production project. Proficiency with UE5 material systems, shaders, and real-time rendering workflows, including the ability to read and write HLSL. Strong understanding of real-time rendering principles, lighting, material behavior, and content production workflows. Experience translating visual direction into technical rendering implementations involving materials, lighting, post-processing, or visual composition. Experience using profiling and performance analysis tools to identify and resolve GPU, shader, memory, and rendering performance issues across hardware configurations. Experience documenting technical solutions and collaborating with artists and engineers to balance visual quality, performance, and maintainability. Preferred Qualifications: Experience adapting rendering solutions across multiple platforms, including quality tiers, feature fallbacks, and performance optimization strategies. Experience developing stylized rendering solutions or rendering systems for characters, environments, visual effects, vegetation, or related visual content. Experience establishing asset standards, rendering guidelines, technical documentation, or performance budget frameworks. Experience implementing and optimizing advanced UE5 rendering features, including Lumen, Nanite, and Virtual Shadow Maps. For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!

Location: Toronto, Canada; New York, United States; Melbourne, Australia; Baku, Azerbaijan; Cairo, Egypt; Dammam, Saudi Arabia Eram Talent is hiring on behalf of its leading Oil & Gas client for multiple professional opportunities across Drilling & Rig Operations, Seismology, Geological Support, Potential Field Services, Technical Support, and Engineering Documentation. The client is seeking qualified and experienced professionals to support drilling operations, rig-site activities, field assignments, geoscientific investigations, technical functions, and engineering project support. Successful candidates will contribute to safe and efficient operations, accurate technical documentation, effective field support, and the achievement of project objectives. Opportunities are available across various experience levels, including operational, technical, specialist, and support roles. Candidates with relevant qualifications and experience are encouraged to apply for the position that best matches their background. Requirements 1. Drilling & Rig Operations Derrickman – Assist with rig-floor operations, handling tubulars and drilling equipment, routine maintenance, and safe execution of drilling activities. Rig Clerk – Provide administrative and clerical support at rig sites, maintaining records, correspondence, employee timekeeping, and site documentation. UR Support Assistant – Support office and field operations through document handling, recordkeeping, equipment and material coordination, and transportation between offices and rig sites. Forklift Operator – Operate forklifts safely to load, unload, transport, stack, and manage drilling materials and equipment in warehouse and site environments. HSE Coordinator – Coordinate health, safety, and environmental activities, including inspections, audits, incident investigations, safety training, risk management, and regulatory compliance. 2. Seismology Seismologist – All Levels (I, II & III) – Monitor seismic survey operations, equipment testing, geophysical data quality, survey positioning, VSP and uphole surveys, and field safety and compliance. Minimum direct experience: 2 years (Level I), 3 years (Level II), and 5 years (Level III). 3. Geological Support Geological Assistant Technician – All Levels (I, II & III) – Support geological field activities through terrain verification, core handling, sample organisation, and proper storage and archiving. Minimum direct experience: 2 years (Level I), 3 years (Level II), and 5 years (Level III). 4. Potential Field Specialists Potential Field Specialist – All Levels (I, II & III) – Support geophysical survey operations through equipment testing, potential-field data quality control, field data processing, sample handling, and verification of survey deliverables. Minimum direct experience: 2 years (Level I), 3 years (Level II), and 5 years (Level III). 5. Technical & Engineering Support Technical Specialist – All Levels (I, II & III) – Perform specialist geophysical technical services, including equipment acceptance checks, survey and data quality control, compliance monitoring, and verification of technical deliverables. Minimum direct experience: 2 years (Level I), 3 years (Level II), and 5 years (Level III). Engineering Support Assistant – Provide engineering project support through technical documentation, drawing and report management, material and equipment listings, data reconciliation, and coordination with engineering and planning teams.

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Every agent on Baseten Sandboxes runs in its own microVM. Agents call models, reach tools and APIs, expose services, and more and more often talk to each other. Networking built into today's cloud providers was not designed for very large numbers of isolated machines that suspend, resume, and exchange data constantly. The Agent Infra team builds its own networking stack for sandboxes, designed from the start for that scale. It runs in user space, with VPP (FD.io http://FD.io) as its main data plane technology, and is built from virtualized network functions (VNF/NFV): carrier-grade, low-latency packet processing designed for very large numbers of agents. In September 2026, Baseten acquired Blaxel https://www.baseten.co/blog/blaxel-is-joining-baseten-to-build-the-future-of-agentic-cloud/, whose sandboxes, storage, and networking are the foundation for Baseten Sandboxes https://docs.baseten.co/sandboxes. You'll build multi-tenant virtual private networking that connects each customer's agents and services privately and securely, using modern overlay technologies. We are building a cloud, not just using one. We want engineers who expose the network as a programmable API and write the code, not operators who push router and switch configuration. The team is small and ownership is big: we ship in weeks and months, not multi-year programs. This role is separate from Baseten's GPU-to-GPU networking. Here you'll own how sandboxes connect to each other, to Baseten services, to customer networks, and to the internet. If you've built user-space data planes, virtualized network functions, or multi-tenant cloud networking and want to design one for agents, we'd love to talk. EXAMPLE INITIATIVES - Blaxel is joining Baseten to build the future of agentic infrastructure https://www.baseten.co/blog/blaxel-is-joining-baseten-to-build-the-future-of-agentic-cloud/ - Securing the open frontier with NVIDIA OpenShell and Blaxel sandboxes https://www.baseten.co/blog/announcing-carbon/ - Baseten Sandboxes documentation https://docs.baseten.co/sandboxes RESPONSIBILITIES - Design and build the user-space, VPP-based data plane that connects microVM sandboxes to each other, to Baseten services, and to the internet - Build multi-tenant virtual private networking and overlays (for example EVPN, GENEVE, VXLAN) across regions - Expose the network as a programmable API that the rest of the platform calls - Cut latency and raise connection scale for agent-to-agent and agent-to-service traffic - Build routing that sends each request to the nearest region and keeps connections working as sandboxes suspend and resume - Build secure ingress and egress for sandboxes, including firewalling, static egress IPs, and custom domains with managed TLS - Build L7 proxies for request inspection, filtering, secret injection, and auditing - Own per-sandbox addressing, including IPv6, and network isolation between tenants - Build observability for the packet path across guest, host, and network, and debug production issues end to end - Work closely with the compute, storage, GPU infrastructure, and datacenter teams REQUIREMENTS - Experience with user-space packet processing (DPDK, VPP, or similar) or virtualized network functions (VNF/NFV) - Experience building multi-tenant networking in production (VXLAN, GENEVE, VRF) - Experience building a software-defined network, overlay network, or packet-processing data plane in production - You write production code: strong systems programming in Rust, Go, and/or C/C++. Network architects are welcome if they build, not only configure - Experience building cloud networking as the provider, not only consuming a cloud provider's network - Solid grounding in TCP/IP and routing - Experience building or operating proxies, load balancers, or L4/L7 gateways at scale - Experience debugging latency and throughput problems with packet captures, tracing, and profiling - You move fast and like owning a problem end to end on a small team NICE TO HAVE - Experience with VPP / FD.io http://FD.io, our main networking technology - Experience with GENEVE or VXLAN overlays and EVPN - Linux kernel networking: eBPF/XDP, netfilter or nftables, network namespaces - Familiarity with virtual machine networking: virtio-net, vhost, TAP devices, or networking for Firecracker or Cloud Hypervisor - Experience running IPv6 at scale - Background in telecom user-plane or 5G core networking, or in low-latency trading networks - Experience with multi-region traffic routing, anycast, or BGP - Experience with TLS termination, DNS, and egress security controls BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Cairo, Egypt Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Help us challenge injustice by creating fair choices for millions of people across in 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary starting from 59 200 EUR gross Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Join the Storefront Team and help build the core customer-facing experience of our marketplace - from discovering partners and browsing product catalogs to product details, cart, and checkout. You’ll work on scalable backend solutions that provide a seamless experience across different partners while improving performance, personalization, conversion, and enabling the rapid integration of new partners. Location: Georgia (country) 🇬🇪 Key Responsibilities Developing backend services for a grocery storefront, including catalog, categories, search, PDP, cart, and checkout. Working with large catalogs and assortments that depend on a specific store, warehouse, or user location. Handling frequently changing prices, inventory, discounts, and product availability. Validating the cart before checkout, including prices, availability, quantity limits, minimum order value, and store restrictions. Supporting grocery-specific scenarios such as weighted products, unavailable items, and substitutions. Integrating with catalog, pricing, inventory, order, payment, and delivery services. Onboarding grocery partners with different APIs and data models. Ensuring low latency, high availability, and resilience of customer-facing flows. Skills, Knowledge and Expertise Mandatory: proven experience in the grocery 5+ years of commercial backend engineering. With experience solving complex problems in high-load environments Strong knowledge of Go programming language. Knows and has applied advanced features of the Go language in practice Strong SQL knowledges, including designing schemas, scaling strategies (replication, partitioning, sharding) and query optimisation for high-load environment In-depth knowledge of Redis, familiar with various data structures, and its efficient use in high-load systems Experience working with Docker, understanding CI/CD pipelines. Knows how work k8s (or analogs) and cloud infrastructure (like AWS) Experience with synchronous and asynchronous inter-service communication patterns, with a focus on reliability in high load environment Knows main microservice architecture patterns. Deep understanding of how to build efficient interactions between client and server applications, knows limitations Proven ability to design and implement a full observability strategy, including metrics, logging, dashboards, and tracing An interest in new technologies, a collaborative spirit, and a drive to continuously develop your skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We're looking for an Infrastructure Security Engineer to secure complex multicloud infrastructure, which runs mostly on Kubernetes. You'll join the security team as a hands-on engineer who builds, not just reviews: security processes, automating checks and working side by side with a team of skilled professionals. InDrive is an AI-friendly company. We use AI tools in daily engineering work and encourage you to use them to automate security operations, speed up reviews and build better tooling. Key Responsibilities Build, maintain and evolve the security of our multicloud environment, Kubernetes clusters and CI/CD systems. Build and maintain vulnerability management processes using commercial and open-source tools, and help engineering teams drive remediation. Contribute to the architectural design of infrastructure services, bringing security expertise across the full lifecycle, from design to production. Run regular security assessments and hardening reviews, and turn findings into secure baselines and guardrails. Automate security checks and operations with code, and use AI-assisted tooling where it makes the team faster. Work with SIEM and monitoring to improve detection coverage for cloud and Kubernetes workloads. Take part in incident response for cloud and Kubernetes environments. Skills, Knowledge and Expertise 3+ years of hands-on experience in infrastructure security, including vulnerability management across cloud and on-prem environments. Strong proficiency with cloud platforms (AWS or GCP) and with Kubernetes: applying security best practices for a high-load production infrastructure. Strong knowledge of IaC tools (Terraform, Terragrunt, Ansible), GitOps (ArgoCD), and CI/CD pipeline security (e.g. GitHub Actions). Understanding of risk based approach to vulnerability management and Cybersecurity in general Automation skills in Python or Bash. Understanding of Zero Trust principles and experience securing remote access with ZTNA solutions. Experience with SIEM solutions. Good written and spoken English. Nice to have Certifications: CKS (Certified Kubernetes Security Specialist) and/or AWS Certified Security – Specialty. Experience with Kubernetes security tooling: policy engines, runtime security and network policies. Hands-on experience with AWS native security services (GuardDuty, Security Hub, IAM Access Analyzer, CloudTrail). Hands-on incident response experience in cloud or Kubernetes environments. Familiarity with secret management tools (e.g. HashiCorp Vault, AWS Secrets Manager). Experience using LLMs or AI agents to automate security workflows Why join us Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 80 000 EUR gross Final benefits may vary depending on the location.

Location: Abu Dhabi, United Arab Emirates Workplace: onsite We are looking for Solution Architect to drive the evolution of our ride-hailing and super-app platform. In this role, you will work closely with engineering teams and the domains directors to define architecture strategy, ensure scalable and resilient solutions, and guide key technical decisions while supporting rapid product growth. Key Responsibilities Participate in system design and architectural decisionmaking in collaboration with development teams, ensuring a balance between speed, quality, and resilience Collaborate with the architecture team to develop a long-term roadmap for the evolution of the platform architecture and technological solutions, enabling scalability and sustainable business growth Conduct audits of key services, identify technical debt, and propose a modernization strategy to support high load and rapid product launches Drive the development of architecture and related processes Define the architectural vision and technical strategy in collaboration with the CTO and other architects Skills, Knowledge and Expertise Experience designing and implementing architectures for highload distributed systems (we handle 230K RPS across 7 regions). Strong understanding of both serverside and clientside architecture and their constraints. Excellent knowledge of modern technologies, particularly AWS: AWS Certified Solutions Architect Associate certification is required. AWS Certified Solutions Architect Professional certification is preferred. Strong leadership skills: able to shape technical vision and effectively communicate complex architectural decisions to both engineers and nontechnical stakeholders. Ability to coordinate architectural collaboration across multiple teams and ensure consistent approaches at the platform level. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid Several Backend Engineer positions are available within product teams. Each role is embedded in a single team and focuses on the development and scaling of backend solutions across the company’s product areas. Key Responsibilities Design and implement complex business logic in Golang autonomously, while ensuring high performance and system reliability. Design optimal database structures (SQL), manage indexes, and optimize query performance. Build asynchronous service interactions using Kafka. Take ownership of backend services lifecycle, including delivery, monitoring and maintaining backend services in the production environment Write clean, structured code, conduct code reviews, ensure compliance with architectural guidelines (ADR), and implement engineering best practices. Set up monitoring and alerting for your services, participate in Post-Mortem processes, identify root causes of incidents, and automate routine tasks. Share expertise with the team, participate in onboarding new members, and contribute to the development of internal libraries and tools. Proactively seek improvements in technical implementations and product solutions, striving to deliver the best possible user experience. Skills, Knowledge and Expertise 6+ years of commercial backend engineering. With experience solving complex problems in high-load environments 3+years of commercial experience with Golang. Knows and has applied advanced features of the Go language in practice Strong SQL knowledges, including designing schemas, scaling strategies (replication, partitioning, sharding) and query optimisation for high-load environment In-depth knowledge of Redis, familiar with various data structures, and its efficient use in high-load systems Experience working with Docker, understanding CI/CD pipelines. Knows how work k8s (or analogs) and cloud infrastructure (like AWS) Experience with synchronous and asynchronous inter-service communication patterns, with a focus on reliability in high load environment Knows main microservice architecture patterns. Deep understanding of how to build efficient interactions between client and server applications, knows limitations Proven ability to design and implement a full observability strategy, including metrics, logging, dashboards, and tracing An interest in new technologies, a collaborative spirit, and a drive to continuously develop your skills Conditions & Benefits Stable salary, official employment. Health insurance. Hybrid work mode and flexible schedule. Access to professional counseling services including psychological, financial, and legal support. Discount club membership. Diverse internal training programs. Partially or fully paid additional training courses. All necessary work equipment.

Location: Almaty, Kazakhstan Workplace: hybrid Several Senior Backend Engineer positions are available within product teams. Each role is embedded in a single team and focuses on the development and scaling of backend solutions across the company’s product areas. Key Responsibilities Design and implement complex business logic in Golang autonomously, while ensuring high performance and system reliability. Design optimal database structures (SQL), manage indexes, and optimize query performance. Build asynchronous service interactions using Kafka. Take ownership of backend services lifecycle, including delivery, monitoring and maintaining backend services in the production environment Write clean, structured code, conduct code reviews, ensure compliance with architectural guidelines (ADR), and implement engineering best practices. Set up monitoring and alerting for your services, participate in Post-Mortem processes, identify root causes of incidents, and automate routine tasks. Share expertise with the team, participate in onboarding new members, and contribute to the development of internal libraries and tools. Proactively seek improvements in technical implementations and product solutions, striving to deliver the best possible user experience. Skills, Knowledge and Expertise 6+ years of commercial backend engineering. With experience solving complex problems in high-load environments 4+years of commercial experience with Golang. Knows and has applied advanced features of the Go language in practice Strong SQL knowledges, including designing schemas, scaling strategies (replication, partitioning, sharding) and query optimisation for high-load environment In-depth knowledge of Redis, familiar with various data structures, and its efficient use in high-load systems Experience working with Docker, understanding CI/CD pipelines. Knows how work k8s (or analogs) and cloud infrastructure (like AWS) Experience with synchronous and asynchronous inter-service communication patterns, with a focus on reliability in high load environment Knows main microservice architecture patterns. Deep understanding of how to build efficient interactions between client and server applications, knows limitations Proven ability to design and implement a full observability strategy, including metrics, logging, dashboards, and tracing An interest in new technologies, a collaborative spirit, and a drive to continuously develop your skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid The QA Load team is responsible for the performance and scalability of services across their entire lifecycle — from Go/No-Go decisions before launch to working with real production traffic. We design and execute load tests, model real-world usage scenarios, identify and eliminate bottlenecks in backend systems, databases, messaging, and infrastructure, and work closely with SRE, DevOps, and product engineering teams. The role focuses on systematic performance improvement: building load-testing infrastructure, automation and CI/CD quality gates, performance analysis and experimentation, and translating technical metrics (latency, RPS, p95/p99) into clear business impact. Our goal is to make performance a core aspect of product quality and ensure the stable operation of high-load, geo-distributed systems. Key Responsibilities Performance Audits & Integration Support: Go/No-Go decisions with our stakeholder about launches services before integrating them into our ecosystem and integrations support (audit APIs, web, databases, caches, message brokers) Design&Execute Load Tests global strategy: Modeling of load testing scenarios (load, stress, soak, peak, find max tests), methodology and formation of non-functional requirements for system using k6, JMeter (DSL framework) Simulate real-world scenarios and traffic patterns to validate systems under production-like conditions (including high RPS, concurrency levels, data skew, and geo-distributed load) Load Modeling: Calculate and validate detailed load models – e.g. expected RPS, concurrent users, transaction volumes, and data distribution. Adjust these models to mirror peak and edge-case scenarios, ensuring our capacity planning is grounded in reality. Bottleneck Analysis & Fixes: Find, analyze, and fix performance bottlenecks. This includes: backend issues (CPU hotspots, memory leaks, GC pauses, thread pool exhaustion) DB inefficiencies (Aurora MySQL/RDS indexing, query locks, IOPS limits) messaging/queue back-pressure (Kafka partitioning, consumer lag, throughput limits) network constraints (latency, load balancer settings, timeouts) Work hands-on with SRE, DevOps, and Backend teams to implement optimizations and verify the improvements. Prepare for Production Traffic: Ensure services are production-ready. Drive capacity planning exercises and stress tests to determine scaling lag/limits and failure modes. Verify that services can gracefully handle traffic spikes or component failures without violating SLAs or SLOs. Help partners configure autoscaling policies for sustained performance Loadtesting Infrastructure Setup&Tuning: Set up, audit, and operate performance testing infrastructure for our services load testing automation and geo-distributed load generator to simulate production traffic Performance Analysis & Experimentation: Approach performance issues with an performance analyst/architect mindset – form hypotheses, design experiments, run tests, and draw conclusions to configuration infrastructure and fix backend code. For example, if latency is high, hypothesize the cause (e.g. database index missing), test the hypothesis, and then make a the fix. Repeat this iterative process to methodically improve system performance. Business Impact Translation: Translate technical performance insights into business risks and opportunities. For instance, demonstrate how reducing latency or improving p95 response time can increase conversion rates or GMV. Communicate these insights to both engineers and non-technical stakeholders to underline the business value of performance work. Observability & Monitoring: Utilize observability tools to monitor performance during tests. Set up dashboards and alerts in Grafana/Prometheus and other systems (e.g. New Relic, Dynatrace, Zabbix, ELK Stack, Coroot), analyze traces and logs. Use few methods to interpret results and guide troubleshooting. Performance Tooling: Build internal performance tooling in Golang: Design and maintain internal tools for automation performance testing and analysis Load as a Service for product teams: traffic generators, load managers, mocks, test stubs, data feeders, and helper services used across partner integrations. Building load test scenarios to Jmeter (DSL framework) and k6 in JavaScript. Innovate on tooling to make load tests easier to create, run, and analyze for the whole team. CI/CD Integration: Integrate performance tests into our CI/CD pipeline as QG. Automate load tests run to every new integration or code change is evaluated for performance regressions. Ensure that build pipelines can catch and flag performance drops (e.g. increased response times, higher resource usage) before changes reach production. Reporting&Communication: Prepare executive-ready performance reports for engineering teams and C-level stakeholders. Highlight key metrics (p95/p99 latency, throughput, error rates, saturation signals) and identify primary scalability bottlenecks across services, databases, caches, and messaging systems, and compare results against SLOs and capacity targets. Provide clear root-cause explanations and actionable recommendations, including performance vs cost trade-offs, to support production readiness and Go/No Go decisions. Performance Culture: Champion a culture where performance = product quality. Educate and influence teams to treat performance testing as an integral, continuous part of the development lifecycle rather than a one-time task. Share best practices and success stories, ensuring that performance considerations are baked into design, coding, and testing processes from the start. Conducting production load and traffic validation experiments with full ownership of risk assessment, blast radius control, observability, and rollback procedures. Work with geo-distributed, high-load systems (200k+ RPS) and latency-sensitive mobile flows Set up production-like performance environments in AWS Conducting and modeling load tests in production Performance analytics → hypotheses → experiments → fixes → measurable business impact (latency, conversion, GMV) Skills, Knowledge and Expertise 5+ years in Performance/SRE/Load Testing Strong programming skills in Golang/Kotlin/Java Strong k6 or JMeter DSL - Performance Testing Mastery: Hands-on expertise with modern load testing tools, especially k6 and/or JMeter (and their scripting DSL). Deep understanding of performance best practice – you know when to apply load testing vs stress testing vs soak testing, and how to interpret the results of each. Hands-on experience with AWS infrastructure on for high-load systems: EKS, EC2, Auto Scaling Groups, ALB/NLB, VPC, subnets, routing, security groups Designing and tuning autoscaling strategies for compute (KEDA/Karpenter/Cluster Autoscaler, EC2 scaling policies) Understanding network performance characteristics: latency, cross-AZ traffic, NAT/egress limits, load balancer behavior under high RPS Profiling Golang, Kafka, Redis, DB tuning experience Automation loadtesting and make QG (JVM languages and Go) SRE mindset (RED/USE, SLO, error budgets) Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Dammam, Saudi Arabia PIPECARE Group is looking for an experienced Rigger Level 1 to join our team in Dammam, Saudi Arabia. By providing technology and service focused solutions to the international arena of the oil and gas industry, the PipeCare Group of companies has been helping our customers ensure the integrity of their pipeline and facility assets for over 25 years. Industry/sector: Oil & Gas / In Line Inspection services. Rigger Level 1 is responsible for planning, supervising, and executing all rigging and lifting activities safely and efficiently. The role ensures that lifting operations are carried out in compliance with company procedures, client requirements, and applicable safety standards. Key Responsibilities & Authorities Perform and supervise all rigging and lifting activities in accordance with approved lifting plans and safety procedures. Inspect slings, shackles, hooks, chains, wire ropes, spreader beams, and other lifting equipment before use. Ensure all lifting gear is properly certified, tagged, and fit for purpose. Determine load weights, center of gravity, and suitable lifting points before lifting operations. Coordinate with crane operators, supervisors, and lifting teams to ensure safe execution of lifting activities. Direct crane movements using approved hand signals and communication methods. Ensure loads are properly secured, balanced, and controlled during lifting operations. Conduct pre-lift inspections and participate in toolbox talks and risk assessments. Monitor lifting operations and stop any activity that presents a safety risk. Report damaged or defective lifting equipment and remove it from service. Maintain lifting equipment records and inspection logs. Assist in loading, unloading, positioning, and installation of equipment and materials. Guide and mentor junior riggers. Report incidents, near misses, unsafe conditions, and operational issues to the supervisor. Following team leader instruction all the time during the activities. Need to submit all lifting plans prior to each activity. Always available to meet the Client schedule. Train other employees when and as required by other team members as per Management. Always notify the line manager for sick leave or annual vacation. Need to attend multiple activities in given single day. Requirements High School Diploma or equivalent. Valid Saudi Aramco Rigger Level 1 certification. Minimum 5 years of experience in rigging and critical lifting operations. Knowledge of lifting equipment, rigging techniques, and load calculations. Ability to read and interpret lifting plans and rigging drawings. Good communication skills in English. Strong understanding of HSE requirements and lifting regulations. Saudi Aramco work experience. Work experience in Hydrocarbon facilities. Must have valid Driving License of KSA.

Location: Arlington, VA, United States Job Title Cyber Virtualization Engineer Why IDS? IDS believes in resolving conflict, building innovative approaches to do so. Combining operational expertise with an intimate understanding of today’s greatest challenges, we bring our customers the solutions required for success in a complex and multidimensional world. IDS tailors solutions for a diverse range of government, military, nonprofit, and public-sector clients. Locations Arlington, VA Shifts Available Please note, candidates must be flexible. Shift times are general hours; some projects may require earlier or later reporting based on customer requirements. Job Description SITE 525 is seeking a highly skilled Cyber Virtualization Engineer to support the development and sustainment of advanced cyber training environments. This role involves hands-on engineering of secure, scalable, and AI-enabled virtual ranges that emulate realistic, adversarial network conditions across IT and OT domains. These environments are used for cyber mission rehearsals, red/blue/gray team operations, and full-spectrum cybersecurity exercises. Must be willing to travel up to 25%. Responsible for designing, deploying, and maintaining advanced virtualized training environments that replicate realistic, large-scale, and adversarial network conditions. This position focuses on engineering and integrating dynamic, hypervisor-driven platforms and virtualization technologies to support cyber mission rehearsals, red/blue/gray team operations, and full-spectrum training exercises. Key Duties Engineer and implement scalable virtualized environments leveraging hypervisors (KVM, VMware, Hyper-V), virtual machines, containers, and software-defined networking across hybrid, edge, and cloud infrastructures. Implement and manage virtualization stacks including private cloud platforms, hypervisor clusters, and orchestration frameworks for large-scale, multi-tenant environments. Develop automation and orchestration tooling for provisioning, snapshotting, and lifecycle management of virtualized assets using Infrastructure-as-Code and CI/CD pipelines. Integrate advanced traffic simulation capabilities (burst, steady-state, geo-distributed, AI/ML-driven) to emulate realistic user and system behaviors within virtual ranges. Build and maintain frameworks and tooling for user and NPC emulation across virtualized environments to enhance operational realism, including threat emulation and defensive toolsets for network monitoring, incident detection, and response. Implement observability pipelines for performance monitoring, traffic replay, autoscaling validation, and centralized logging in production-grade virtual infrastructures. Administer and secure hypervisor platforms and virtual networking components, ensuring isolation, resiliency, and compliance for mission-critical environments. Manage network and server infrastructure including Active Directory, identity management systems, and virtualized security controls. Integrate third-party virtualization and orchestration tools to improve fidelity and scalability of training environments. Support exercise operations including setup, execution, troubleshooting, and real-time scenario management for White Cell operations. Collaborate with technical working groups and stakeholders to validate and enhance virtualization strategies for cyber training environments. Apply knowledge of OT systems (SCADA, ICS, PLCs, IoT/IIoT) within virtualized contexts for realistic emulation. Relevant Technologies & Tools: Virtualization & Hypervisors: VMware ESXi/vSphere, KVM/QEMU, Microsoft Hyper-V, Proxmox, OpenStack Virtual Infrastructure Management: VM lifecycle management, snapshotting, cloning, orchestration frameworks Cloud & Containerization: Private cloud platforms, AWS, Azure, Kubernetes (K8s), Docker, Podman, hybrid and edge deployments Networking & SDN: Virtual switches (vSwitch, vDS), software-defined networking, network segmentation, VPNs, dynamic Network-as-Code tools Automation & IaC: Infrastructure-as-Code (Terraform, Ansible, Packer, Helm, Nomad ), CI/CD integration for infrastructure Performance & Observability: Metrics collection, centralized logging, traffic replay, load simulation, autoscaling validation Security in Virtualized Environments: Identity management, Active Directory (GPOs, tiered admin scripts), secure isolation of virtual ranges Cyber Range Engineering: Virtualized cyber training environments, adversarial network simulation, AI/ML-driven traffic emulation Traffic Simulation & User Emulation: Lariat, CMU GHOSTS, MITRE Caldera, Red Canary, Atomic Red Team, TRex, BreakingPoint, Locust, k6, custom Python/TypeScript scripts, AI-enabled agents Compliance & Assurance: NIST 800-series, ISO 27001, FedRAMP, CUI-compliant controls Monitoring & Control Interfaces: Custom dashboards for exercise operations, centralized scenario orchestration Requirements Bachelor’s or Master’s degree in Cybersecurity, Computer Engineering, or related field. 5+ years of experience in cyber engineering, network operations, or cyber range development. Top Secret security clearance. Proficiency in virtualization, containerization, and cloud technologies. Experience with offensive and defensive cybersecurity tools and frameworks. Familiarity with AI/ML integration in cyber environments. Strong scripting and automation skills (e.g., Python, Bash, PowerShell). Experience with infrastructure-as-code tools (e.g., Terraform, Ansible). Knowledge of OT systems and protocols. Security certifications (e.g., CISSP, CEH, OSCP) are a plus. Compensation Competitive Hourly Pay Benefits Questions? Please reach out to lolney@idsinternational.com for additional questions or information.