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Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Corporate Counsel, Intellectual Property Enforcement San Mateo, CA | Hybrid - 2 days per week in our San Mateo office Role Summary: Sony Interactive Entertainment’s Legal, Public Policy & ESG team is looking for an experienced lawyer to join its award-winning IP Enforcement practice. This role combines sophisticated and technically complex copyright and content protection work with online and offline enforcement, addressing evolving issues such as piracy, pre-release leaks, game modifications, circumvention, emulators, and other emerging threats affecting PlayStation games and content. As Corporate Counsel, IP Enforcement , you will serve as the primary legal contact for IP enforcement in the Americas, with a particular focus on supporting PlayStation Studios and SIE’s Game Protection Program, our dedicated initiative to combat piracy, protect pre-release content, and address unauthorized game modification. Reporting to the Director, Global IP Enforcement in the UK, you will work closely with legal, technical, investigative, security, fraud, and business teams around the world. This is a highly collaborative role offering a mix of contentious, advisory, and strategic work at the intersection of intellectual property, entertainment, video games, and technology. What You’ll Be Doing: Game Protection & Studio Support Serve as lead legal counsel for SIE’s Game Protection Program in the Americas, developing strategies to combat piracy, respond to pre-release content leaks, and address unauthorized game modifications affecting PlayStation titles. Partner directly with PlayStation Studios and production, security, and release teams to identify content-protection risks and develop proactive strategies throughout the game development and release lifecycle. Provide practical and strategic copyright advice, particularly relating to the Digital Millennium Copyright Act (DMCA), including notice and takedown procedures, counternotices, safe harbors, repeat infringers, fair use, and complex or contested matters. Advise on emerging and technically complex copyright issues involving game modifications, user-created and unauthorized in-game content, emulators and ports, infringing apps and services, unauthorized distribution, and circumvention of technological protection measures. Help develop practical policies and scalable approaches as these issues evolve across PlayStation Studios and platforms. Work with investigators, technical and security teams, data specialists, outside counsel, and other partners to develop evidence and translate legal and technical intelligence into effective enforcement action. IP Enforcement Support the IP enforcement needs of SIE’s hardware and merchandise businesses in the Americas, developing practical strategies to protect PlayStation products and intellectual property. Help shape SIE’s broader Americas enforcement strategy, using data and intelligence to identify significant infringers, enforcement gaps, and opportunities for targeted action. Support anti-counterfeiting efforts across online and physical channels, including marketplace enforcement, investigations, cease-and-desist activity, Customs and border enforcement, administrative and criminal actions, and escalation to litigation or law enforcement when appropriate. Take an active role in online enforcement across e-commerce marketplaces, social media, websites, apps, and other digital services. Strategic & Cross-Functional Partnership Partner with colleagues across SIE’s IP Litigation, Brands, and Patent teams on significant enforcement matters, including strategic litigation and design-related enforcement. Monitor developments in copyright, intermediary liability, anti-counterfeiting, digital enforcement, and relevant technologies, advising the business on their potential impact. Develop enforcement policies, playbooks, procedures, and best practices, and provide practical guidance and training to internal stakeholders and external partners. Use enforcement data and reporting to identify trends, emerging threats, and opportunities to strengthen SIE’s enforcement programs. Represent SIE, where appropriate, in industry organizations and initiatives relating to copyright, content protection, anti-counterfeiting, and IP enforcement. Work collaboratively with SIE’s IP Enforcement paralegals in the US and UK, providing legal guidance and supporting their continued development. What We’re Looking For: A qualified lawyer with approximately 6–12 years of post-qualified experience in intellectual property enforcement, gained in-house and/or in private practice. J.D. from an accredited U.S. law school. Current member in good standing of a U.S. state bar; California Bar membership preferred. If not admitted in California, must be eligible to obtain Registered In-House Counsel status in California promptly upon hire and maintain that status throughout employment. Strong knowledge and practical experience of U.S. copyright law and the DMCA, including online enforcement, notice and takedown processes, counternotices, safe harbors, fair use, and intermediary liability. Experience developing and executing IP enforcement strategies, ideally involving online enforcement, investigations, anti-counterfeiting, and escalation to litigation or law enforcement. Experience with, or strong interest in, digital piracy and technically complex copyright matters. Experience involving video games, software, apps, game modifications, circumvention of technological protection measures, or similar digital content issues is particularly valuable. Strong legal judgment and a pragmatic approach to enforcement, with the ability to prioritize high-impact matters and balance legal risk, enforcement objectives, and commercial considerations. Ability to work effectively with technical, investigative, and business specialists and translate complex information into practical legal strategies. Excellent communication and collaboration skills, with the independence and flexibility to operate effectively across regions, cultures, and time zones in a global organization. Strong technical curiosity and an interest in video games and interactive entertainment, with the ability to understand how games, platforms, and related technologies operate and translate that understanding into practical copyright and enforcement advice. Additional Experience That Would Be Valuable Experience advising on video games, software, digital content, or other technology products, particularly involving game modifications, emulators, piracy, pre-release content protection, or technological protection measures. Experience with game or content protection programs, including pre-release leak response, game security, DMCA anti-circumvention, or other technically complex copyright enforcement matters. Experience working with online marketplaces, platforms, intermediaries, or specialist enforcement providers on copyright, trademark, or anti-counterfeiting matters. Experience with IP enforcement in China, including online or offline anti-counterfeiting, investigations, administrative enforcement, or litigation. Familiarity with design law and design-right enforcement, including design patents and/or registered designs. #LI-SF! At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $209,800 — $314,600 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team The Integrity and Attestation team's remit is to prove what is running at Anthropic: what code it is, where it came from, and whether the machine underneath it is in a known-good state. We build the systems that cryptographically verify build artifacts, model weights, and machines, from hardware roots of trust through firmware and boot to the credentials a workload receives. We also secure the management plane of our servers. These controls protect our model weights and customer data across cloud providers and bare-metal AI data centers, including sites operated by partners. We are hiring an Engineering Manager to lead this team. Anthropic is bringing up new compute quickly, across new hardware platforms and new partners, and each one has to meet the same bar. In this role you will set the team's charter, practices, and priorities. You will partner with our infrastructure, data center, and hardware teams, as well as outside vendors, so that integrity is designed in rather than added later. The goal is simple to state: a machine gets secrets and workloads only after it proves it should, and a new site reaches that bar without slowing down compute. About the role Own the integrity roadmap: threat model from silicon and firmware up through the operating system and workloads, decide what to build, and deliver it Be able to reason about the design and implementation of remote attestation, measured and verified boot, hardware roots of trust (TPM, SPDM), machine identity, and the reference values that define known-good Make attestation the default path, so machines receive credentials and join clusters only after proving their firmware, system software, and security configuration, with no human in the loop Build provenance for what we deploy: signed build artifacts and model weights, independent verification, and tamper-evident transparency logs Lead the protection of sensitive data in use and at rest, including encryption and the chokepoints that control access to it Secure the server management plane across every site: scoped and audited access to baseboard management controllers and management of per-device credentials Make security repeatable as compute grows, so a new site or hardware platform inherits these controls in hours, not weeks Join compute bring-up, data center, and hardware teams at design time Define clear ownership with partner teams: when operations move to another team, your team keeps the security properties and can prove they still hold Own the integrity evidence for our security goals and compliance: the invariants hold, and you can prove it Hire, grow, and retain senior security software engineers; own their career development, and set the practices the team runs on as it scales Who you are Low ego, high empathy; has built diverse teams and has former reports who would vouch for them. Experience managing infrastructure or security engineering teams, including hiring, developing, and managing senior and staff engineers Has grown engineers into staff or lead roles, and experience with performance management Created and maintained a high performing in hypergrowth environments. Kept a team intact and delivering through reorgs, charter changes, or leadership turnover Experience owning a security or infrastructure domain end to end: setting multi-year strategy, delivering year-long cross-organizational work with little direction, and answering to executives for its risk and tradeoffs An appreciation for distributed systems and properties beyond security, including reliability, efficiency, and maintainability Scaled a team and its systems together through hypergrowth, where last quarter's architecture was already too small Hands-on engineering in at least one of: platform security, secure boot and firmware, hardware roots of trust, confidential computing, or software supply chain integrity Threat modeling and risk assessment for systems that span hardware and software, with strong security judgment and pragmatism Comfortable leading through ambiguity with multiple partner teams and outside vendors, where you don't control the hardware or the schedule You may be a good fit if you have: At least 5+ years managing engineering teams and 8+ years hands-on in platform, infrastructure, or security engineering Built or operated remote attestation, device identity, or fleet-wide boot integrity at production scale Worked with BMCs, Redfish, GPU or accelerator attestation, or large-scale bare-metal provisioning Experience with Nitro, SEV-SNP, TDX, or similar confidential computing platforms Built signing, provenance, or transparency systems such as Sigstore, SLSA, or binary transparency Designed key management or offline ceremonies for high-value secrets Worked in high-assurance environments where controls had to be evidenced, not just deployed Taken infrastructure from zero to one and then to maturity: built the first version where nothing existed, then run and hardened it into a system other teams depend on Built or rebuilt a hiring loop and held the bar while adding headcount quickly Pragmatic and steady: cares about unblocking research, product and compute as much as a clean architecture, and brings patience and judgment to opinionated senior engineers Clear and persuasive communicator in writing and in person Familiarity with AI security and safety concepts The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

We’re looking for a Senior Product Builder to own the backend and architecture that let Hub manage a whole fleet of clusters. Your first focus will be the mechanism that sends access, secret, tenant and licence changes out to every connected cluster and brings deployments, health and audit records .

Location: United States Senior Engineering Manager, Data & AI Lead the engineering team behind Foundry, Insights, Intel, and Voice: the agents, analytics, and data intelligence of the modern freight platform. About the Role Remote, United States. Some travel is required for team onsites, customer visits, and industry events. Relocation assistance is not provided. The Senior Engineering Manager, Data & AI leads the engineering group behind Foundry, Insights, Intel, and Voice. You'll own the group's technical strategy, delivery, and quality, hire and develop its engineers, and stay hands-on by prototyping, writing evals, reading traces, and reviewing architecture in depth. The team is about eight engineers today and growing. It also owns the shared foundation those products run on: a context graph that connects loads, trips, carriers, drivers, customers, documents, and conversations; event-sourced platform data streaming into the warehouse; and the evals, tracing, guardrails, and model routing every agent depends on. Alvys facilitates more than $1 billion in funds every month across invoices, carrier payments, and driver settlements. Behind that volume is one of the richest operational datasets in freight. This team turns it into agents that do real work and intelligence customers can't get anywhere else. Engineering leaders at Alvys are builders. Expect to spend about a third of your time building. You'll set the standard for how an AI-first team works: coding agents in the daily workflow, evals before scale, and production evidence over demos. The platform runs on .NET (C#, and increasingly F#), TypeScript, and Python on Azure and AKS, with Cosmos DB, Postgres, Elasticsearch, Snowflake, dbt, and Fivetran underneath. We're looking for someone who treats AI as a first-class material, both in what we build for customers and in how the engineering team works. Industry Insight Freight runs on phone calls, emails, PDFs, and tribal knowledge. The U.S. trucking industry is worth approximately $1 trillion today and is projected to grow by roughly 60% to nearly $1.5 trillion over the next decade. Yet the work that moves that freight is still largely manual. Nearly 580,000 active U.S. motor carriers operate in a highly fragmented market; 91.5% run 10 or fewer trucks, and 99.3% run 100 or fewer. Few of these businesses will ever build a data team of their own. Every check call answered, rate confirmation read, and exception caught by software is time back for a small team running on thin margins. Freight data is also structurally messy. A single load spans brokers, carriers, drivers, shippers, and documents, each with its own identifiers, and the truth lives across EDI messages, phone calls, and free text. Generic AI tooling doesn't model any of this. That's why we're building a context graph grounded in how freight actually moves. Agents can now answer the phone, read documents, query operational data, and take actions inside a TMS. In freight, those actions move trucks and money. They must be correct, auditable, and safe. About Alvys Alvys is building the operating system for modern freight. Our AI-powered, cloud-native platform brings dispatch, driver mobile, safety and compliance, billing and settlements, native EDI, reporting, integrations, and automation into one product. We were founded in 2020 by freight industry insiders who were tired of software built by people who had never moved a load. That combination of deep customer empathy and ambitious technology still defines us. We visit customers, learn how the work actually happens, prototype quickly, debate ideas openly, and turn the best ones into products people rely on. More than 3,000 trucking and brokerage companies use Alvys today, including larger fleets with increasingly sophisticated operations. We've raised $77M to date, including a $40M Series B. That gives us real momentum and room to make bold bets, while remaining early enough that a great engineering leader can materially shape the product, team, and company. We are building more than a modern interface for a traditional TMS. Foundry, our agent platform within Alvys, helps freight teams make decisions and complete work, and this team builds it. You'll work with curious, direct, low-ego people who solve hard problems, move quickly from prototype to production, and measure customer impact. Our Principles AI makes building cheap. It does not make judgment cheap. The constraint has moved from writing code to deciding what to build and proving it is right. Agents belong in the middle of the pipeline. People remain accountable at both ends. These principles turn that into how we work every day. Own the outcome You own what you ship. "AI wrote it" is not an answer. Judgment stays human. People decide what matters and whether the result is correct. Verify independently Generation and verification are separate. Tests, review, and approval run independently of the agent that did the work. Autonomy is earned per workflow. Agents advance only on measured precision against human-verified outcomes. No number, no promotion. Design for control AI-first means security-first. Customer data stays on approved infrastructure under managed identity. Cost is an engineering constraint. Every shared workflow has termination conditions and bounded fan-out. Build durable systems Knowledge is tool-agnostic. Reviewed intent lives once; vendor-specific machinery is generated from it. Multiple vendors are a design assumption. Durable workflows don't couple to one model or harness. Twice is a pattern. Automate repeated work and share it within 48 hours. The Data & AI Portfolio The Data & AI portfolio covers Foundry, our embedded automation and agent platform, including a unified agent chat that answers questions and takes actions; Insights, conversational analytics grounded in each customer's own operating data; Intel, proprietary data intelligence drawn from third-party, licensed, and proprietary data sources; and Voice, AI voice and chat agents for load status, driver check calls, and the follow-ups in between. It also includes the shared foundation: the context graph, the data platform that feeds it, and the evals, tracing, guardrails, and model routing behind every agent. Why This Role Few engineering leadership roles combine frontier AI work, a proprietary dataset, and an industry this underserved. This one does. You build at the frontier, in production. Context graphs, self-learning agents, voice agents, and agentic automation are still being figured out across the industry. Here you ship them to real customers, on live freight operations, not benchmarks. You work with data no one else has. More than 3,000 trucking and brokerage companies run on Alvys, and more than $1 billion in funds moves through the platform every month. Combined with third-party and licensed sources, that data is the raw material for intelligence no single fleet or brokerage could build alone. Your work changes how an industry operates. With 91.5% of carriers running 10 or fewer trucks, most of our customers will never hire a data team. The agents you build give a small business the leverage of a much larger one. You own a portfolio, not a feature. Four products share one platform. You set its architecture, choose its models and vendors, and decide where the team invests as it grows. You shape the team from the start. The group is about eight engineers today. You'll hire the next wave and set the standard for how an AI-first engineering team works at Alvys. You stay close to the decisions. You report to the Head of Engineering, work directly with customers and our Forward Deployed Engineering team, and have a direct line into company planning, backed by a $40M Series B. What You'll Be Responsible For Leading and Growing the Team Manage, coach, and develop a team of about eight engineers, including senior engineers and tech leads, and grow it as the portfolio expands. Hire senior and staff engineers, and keep the quality bar high as the team scales. Run the team AI-first, with coding agents in the daily workflow and clear standards for how AI-written code is reviewed, tested, and shipped. Owning Technical Strategy Set technical direction for agents, data, and the context graph, and make the build, buy, and model calls with cost, quality, and speed in view. Make tradeoffs across four products that share one platform, including what gets built, what gets cut, and where the team invests. Building Agents That Learn Own the agent development lifecycle from prototype to production to continuous improvement. Build self-learning loops so agents improve from outcomes, user corrections, and transcripts, and make that improvement measurable. Make evals a release gate. No agent ships without tests for quality, safety, latency, and cost. Data and the Context Graph Own the context graph that links loads, trips, carriers, drivers, customers, documents, and conversations, and the entity resolution that keeps it trustworthy. Partner on the data platform that feeds it, including event streams, CDC into Snowflake, data quality, and lineage, so agents and analytics share one source of truth. Capture decision traces (the inputs gathered, the rule applied, any exception, who approved it, and why) so precedent becomes searchable for agents and people, while rules stay explicit. Combine third-party, licensed, and proprietary data sources into intelligence customers can act on, with the provenance, licensing terms, and tenant boundaries of each source respected. Safety, Isolation, and Reliability Design agents that change data with scoped permissions, human approvals, and audit trails, and defend against prompt injection and tool misuse. Enforce tenant isolation and least privilege across every agent, tool, and data path. Own reliability and unit economics. Track cost per task, per call, and per tenant, and keep margins healthy as usage grows. Staying Hands-On Spend about a third of your time building: prototype, write evals, read traces, and debug production. Review your team's designs and code with real depth, and stay current on models and tools, separating what works in production from what demos well. Cross-Functional Partnership Work as a peer to product and design leadership on direction, architecture, sequencing, and delivery. Work directly with customers and our Forward Deployed Engineering team, and turn repeated patterns into platform features. The AI Fluency We Expect We measure AI fluency by how you verify, not by how much you use AI. More autonomy is not always better. You match the level of autonomy to the risk of the work, and you hold yourself and the team to the same five competencies. Delegation: You decide whether to use AI at all, which task to hand off, and how much autonomy it gets. Description: You state goals, requirements, and limits clearly, from a single prompt up to project instructions, specs, and policy. Discernment: You check output against evidence: diffs, acceptance checks, evals, and production monitoring. Diligence: You own the effects, including data access, permissions, memory isolation, budgets, and kill switches. Systems: You know how models, context, tools, harnesses, and memory work, and where each one fails. How You Work With Agents Design multi-agent systems on paper before you build them. For each step, choose a rule, a small model, a frontier model, or a person, and measure cost per outcome, not cost per token. Start from code-orchestrated workflows and add model-led autonomy only where the task needs exploration. Keep agent-to-agent handoffs few, and give each agent a contract: inputs, allowed tools, and output schema. Put limits in code, not in prompts: hooks, sandboxed worktrees, and a stop condition, retry cap, and budget on every loop. Separate the agent that writes from the agent that checks, and give the checker fresh context. Work in an explore, plan, execute, verify, and compound rhythm, where every correction becomes a rule, skill, hook, or test. Move fluently across Claude Code, Codex, and Cursor, and choose an editor-first or agent-first surface based on who should hold the controls for the next step. Where You Take the Team Bring every engineer to running goal-based loops, where specs and checks are written first, never weakened to pass, and run by the agent itself. Move the team from steering every turn to designing the system that steers the agent: its context, its harness, and its loop. Build toward agents that run continuously in hosted sandboxes, each with its own least-privilege identity, a named owner, a budget, and a tested kill switch, with risk-scaled human review on financial actions, auth, settlements, and customer data. Close the improvement loop. Capture traces, run error analysis on real failures every week, encode the fixes, and gate every change to rules, memory, or evals behind evals and a human approver. Self-improving never means self-approving. Minimum Qualifications 8+ years building software, including 3+ years managing engineers. You've grown senior engineers and tech leads and remain a hands-on builder who can prototype, debug production, and review code credibly. Production LLM systems. You've shipped LLM-powered products to real users, not demos, and can explain what broke, what you measured, and what you changed. Agentic engineering in your own work. You build with coding agents every day and can show the multi-agent workflows, contracts, hooks, and loops you put into production, and the checks that kept them honest. Depth in agent systems. You've built with tool use, function calling, MCP, orchestration, memory, and retrieval, and you understand where agents fail. Evaluation discipline. You've built eval systems that combine offline suites, online metrics, human review, and transcript analysis, and used them to gate releases. Strong data engineering judgment. You've worked with event streams, CDC, cloud warehouses, dbt, and data quality, and you know how the shape of the data limits what models can do. Distributed systems in production. You've designed and operated production services with real reliability requirements. Multi-tenant security. You've secured multi-tenant SaaS and isolated customer data, and you treat agent permissions as a security boundary. Language fluency. You write Python or TypeScript fluently and are comfortable reading C#, F#, and .NET. Experience with F# or another functional language is a plus. Startup-stage fit. You've operated at Series B/C velocity amid ambiguity, thin support, competing priorities, and a bias toward shipping and learning. Clear technical communication. You can explain a tradeoff to an engineer, a customer, and an executive. Preferred Qualifications Knowledge graphs, context graphs, entity resolution, or GraphRAG in production. Real-time voice agents, including telephony, speech-to-text, text-to-speech, turn-taking, and latency budgets. Fine-tuning, reinforcement learning from feedback, or prompt optimization against eval sets. Embedded automation or workflow platforms such as Activepieces, n8n, or Temporal. SRE experience, or a record of running systems other teams depend on. Logistics or freight experience, or another vertical where data is deeply entangled with operations. Founder or early-stage engineering leadership experience. A history of hiring, growing, and retaining excellent engineers. Built by people who've moved freight. Come build the intelligence layer with us. Learn more at alvys.com

Location: Amsterdam Workplace: OnSite ABOUT US: Tebi is creating the first Connected Restaurant Management System that makes hospitality flow. In one seamless platform, Tebi embeds sales, reservations, kitchen prep, payments, and all the data that powers it, creating smooth service and intuitive insights. Founded by Arnout Schuijff, co-founder of Adyen, and backed by €50 million in funding from Index Ventures & CapitalG, Tebi is built in service of hospitality first. Thousands of restaurants, cafés, bars, and coffee shops across the Netherlands, UK, Italy, Spain, Germany, Denmark and Finland already love running on Tebi.   ABOUT THE ROLE: We’re looking for a Senior AI Engineer to build and run the agents at the heart of Tebi OS. You’ll design, ship, evaluate and scale our Product Agents, along with the data pipelines, tools and infrastructure that make them reliable in production. The ideal candidate started in data or ML engineering and has since moved into AI engineering, building LLM-powered agents for real users. You enjoy turning messy financial and operational data into context an agent can reason over and act on with confidence and you are passionate about solving product challenges through AI. You’ll work closely with product and engineering to put intelligence into the hands of hospitality teams. That could be an agent that answers questions about a restaurant’s finances in real time, one that automates repetitive back-office tasks, or internal tools that help us move faster. WHAT YOU’LL DO: - Design, build and operate production agents: orchestration, tool and function calling, memory, multi-step reasoning, and integration with Tebi’s backend services - Build the data foundations agents rely on, including real-time and batch pipelines over financial and operational data, retrieval layers, and well-modeled datasets agents can query safely and accurately - Turn APIs and internal services into well-defined agent tools, and own the contracts between agents and the rest of the platform - Set up evaluation for agent behavior: offline eval sets, LLM-as-judge and human review, regression testing on prompt and model changes, and feedback loops that improve agents over time - Own observability for agents in production by tracing sessions, tool calls and model calls, and tracking latency, cost, error rates and quality - Work with product teams to find where agents can meaningfully improve the customer experience or internal workflows, and say clearly where they can’t - Make sure agents handle data securely and responsibly, with sensible guardrails, access controls, and protection against prompt injection and data leakage WHAT YOU’LL BRING: - 7+ years in software engineering, with a solid base in data or ML engineering - Hands-on experience building and shipping LLM agents to production, not just prototypes. You’ve dealt with flaky tool calls, runaway loops, hallucinated arguments and token budgets, and you have opinions on how to handle them. - Strong data modeling and data warehousing fundamentals, plus experience with ingestion, transformation and data quality - Strong SQL, and experience with pipeline tools (e.g. Airflow, dbt) and analytical or cloud data platforms (e.g. ClickHouse, BigQuery, Snowflake) - Experience evaluating and monitoring LLM systems, and an understanding of the full lifecycle from experiment to deployment to ongoing improvement - Backend engineering skills: you’re comfortable building the API endpoint that exposes an agent’s output to the frontend, or the service an agent calls as a tool - Clear communication, including the ability to explain trade-offs in latency, cost, accuracy and complexity to product partners - A product mindset. You care about how your work lands with users, and you’re keen to meet customers face to face to understand their needs. This probably isn't the role for you if you have been working with AI agents to improve your day to day working flows but you haven’t built an Agent in the production. People who succeed at Tebi are independent, curious and passionate about hospitality. If this speaks to you we can be the right fit. Learn more about how we work from our Recipe here: https://www.tebi.com/gb/careers . BENEFITS: - Start-up Equity - Competitive Salary - Lunch Provided in Office - Team building events - Unlimited time off What is Restaurant Software? Restaurants and other merchants use various software systems such as Point of Sale (POS), Reservations, Kitchen Display Systems (KDS), Payments, Inventory, Staffing, and the list goes on. These systems all need to speak to each other which they frequently don’t. It’s a mess, and we are fixing it. From buying a croissant at a cafe to having dinner with friends, it’s a €4 Trillion+ global market and a critical part of everyday life in today's economy. How we use AI at Tebi We use AI the way our merchants use Tebi, to cut out the friction and get to what matters faster. We believe in a world where AI increases quality, efficiency and speed. At Tebi, AI isn't a policy or a checkbox, it's just part of how we work. It helps us write, analyse, build, and improve but doesn’t make the last call. If there's a smarter way to do something, we want to find it.

-Проектирование, разработка и поддержка backend-сервисов на NestJS и TypeScript. -Разработка и развитие микросервисной архитектуры, обеспечение отказоустойчивости и масштабируемости.

Location: Almaty, Kazakhstan Workplace: hybrid We’re looking for a Safety Governance Manager to build and own how safety is governed across inDrive’s platform. You’ll set the framework, metrics and reporting that turn safety work into measurable outcomes for riders, drivers and couriers in 47 countries. You’ll work closely with Product, Operations, Legal and Data teams, and report safety performance up to senior leadership and the board. Key Responsibilities Design and launch inDrive’s safety governance framework from the ground up: policies, standards, risk register, controls and review cadence. Verification and reporting. Verify that safety processes and product features work as described. Verify the integrity of safety metrics: review against the approved methodology and independently re-sample incidents with direct access to the underlying data. Return gaps to control owners for remediation, and deliver findings to the senior management through a set reporting cycle. Design the methodology and format for the verification and reporting Safety decision tracking. Design and maintain the risk-acceptance register. Assess each entry against the safety risk appetite statement and report the state of the register to senior management. Safety spend baseline and gap review. Review the safety spend baseline and the costing methodology. What this role does not do. Safety Governance does not own, operate or deliver safety controls; does not set the taxonomy, classification, methodology or other business standards it verifies against; does not accept safety risk; and does not decide how safety controls are resourced. Skills, Knowledge & Expertise 5+ years in trust & safety, safety operations, risk assurance or compliance programme management Experience building a function, methodology or programme from scratch in at least one role Strong governance background, including risk management frameworks and board-level reporting Data literacy: you can specify metrics, challenge a dashboard and interpret a sampling result Hands-on AI fluency (Claude or similar): you can quickly build clear visualisations and storylines that explain complex safety risks in simple terms to any audience Enough legal literacy to work effectively with counsel (a law degree is not required) Strong stakeholder management across Product, Operations, Legal and Data teams in a global environment Strong interpersonal skills: you stay calm and attentive in difficult conversations, can deliver unwelcome QA findings to process owners, and persuade teams outside your authority to act on them Fluent English Strong plus: Experience in ride-hailing, mobility, delivery or another business with offline safety risks Hands-on experience designing or managing an incident taxonomy TSPA (Trust & Safety Professional Association) membership A certificate in data analytics 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: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE The Robotics Applied Research Lead establishes and leads Humanoid’s AI research and engineering function. You decide which Physical AI data problems we work on, define how we test them, and stay directly involved in the most important technical work. You connect four areas that often sit apart: 1. Multimodal and embodied data 2. Transformer-based models and how data impacts robot policies 3. Rigorous offline and real-world evaluation of policies 4. Deployment of models in the data ecosystem This is a player-coach role. In the first year, at least half of your time is direct technical work: designing models and experiments, reviewing or writing code, inspecting data, debugging training, examining failures, and reviewing robot rollouts. You will also build a small research and engineering team. Add people only when the work requires them. MANDATE Turn Humanoid data and technical access into measurable advances in Physical AI systems. You own the answers, and the evidence, to questions such as: - Which model families should we train, adapt, or evaluate? - Which data produces meaningful gains in robot performance? - What coverage, sensors, annotations, and quality controls do the models require? - Which offline measurements predict real-world robot performance? - Where should we adapt existing open models rather than train from scratch? - What should Humanoid build itself, and what should it reuse or obtain through partners?   WHAT YOU'LL DO - Set the technical direction: Define a focused research and engineering roadmap. Select a small number of high-value bets with clear hypotheses, baselines, milestones, and stop criteria. Decide what we build, adapt, license, or access through partners. Drop work that no longer has a strong case. Likely scope includes vision-language-action models, multimodal Transformers, robot foundation models, action representation, imitation and reinforcement learning, world models, cross-embodiment transfer, data-efficient adaptation, and robot-policy evaluation. - Own Transformer research and engineering: Design, adapt, train, and evaluate Transformer-based systems for embodied tasks. Make the architecture and training decisions yourself. Start from strong existing models and baselines. Train from scratch only when evidence supports the cost. Build or review the critical code. - Connect models to data strategy: Define the data needed to train and evaluate the selected models. Specify sensors, modalities, annotations, mixtures, and quality controls. Measure the effect of data quality, diversity, and composition on model behavior. Distinguish data volume from data value. You set technical data requirements; you do not run annotation workforces or field collection. - Own evaluation: Establish offline and real-world evaluation systems, baselines, held-out conditions, and release gates. Guard against leakage, overfitting, and weak success definitions. Compare offline metrics with real-robot outcomes. A benchmark score alone is not a successful result. The evaluation must support a decision. - Move work onto physical systems: Take projects from problem definition through training, hardware integration, and real-world testing. Design safe test plans and staged deployment. Analyse failures across data, perception, model, control, hardware, and environment. Validate material claims on physical systems. - Build a small technical team: Recruit a few complementary researchers and engineers. Lead architecture, experiment, code, and failure reviews. Keep the team focused on validated results, not paper count, benchmark theatre, or headcount. - Represent the function and own responsible development: Explain the strategy to customers, partners, and investors. Convert customer needs into testable technical requirements. State uncertainty and limits clearly. Define safety constraints, supervision, and rollback paths for physical trials. Require reproducible evidence before making capability or safety claims.   WHAT WE'RE LOOKING FOR - Deep, direct Transformer expertise: This is a hard requirement. You must have personally made material architecture or training decisions in one or more substantial Transformer-based systems, such as vision Transformers, VLMs, VLAs, multimodal foundation models, Decision Transformers, diffusion Transformers, video Transformers, world models, or Transformer-based perception, planning, or control. You should be able to explain, in detail, how you represented inputs and outputs, tokenized data, fused modalities, structured attention and temporal context, chose losses, built the data mixture, distributed and monitored training, diagnosed failures, and what you personally changed and why it affected task performance. Using hosted model APIs, prompting language models, or running an unchanged public training recipe does not meet this requirement. - Physical AI or embodied-system experience: You have worked on machine learning for a system that perceives or acts in the physical world: robotics, autonomous vehicles, drones, industrial automation, manipulation, mobile robots, humanoids, wearable or egocentric systems, or similar. At least one substantial project progressed beyond an offline dataset into a real or operational physical system. Simulation-only experience is not sufficient unless you also owned credible sim-to-real transfer and physical validation. - Hands-on technical ability: You write and review high-quality Python. You work directly with PyTorch or an equivalent framework. You can read unfamiliar model and training code, design and debug experiments, inspect failures and rollout traces, work with large multimodal datasets, and make informed decisions about compute, memory, latency, and cost. - Technical leadership: You have set direction for important technical work: a research or engineering group, a major model or robotics programme, or a cross-functional project you owned. You have hired or mentored researchers or engineers, made architecture and resource decisions, stopped weak work, and taken a result into deployment. A management title is not required. Direct ownership is. - Evaluation, communication, and judgment: You design held-out tests, run controlled comparisons, find leakage and confounds, and report results with appropriate uncertainty. You separate evidence from belief, state what remains unknown, and reduce broad research questions to testable work. - Strong preference - Computer Vision: We are particularly interested in candidates who combine deep expertise in Transformer architectures with a strong background in computer vision. Relevant experience may include visual representation learning, vision-language models (VLMs), video and temporal modelling, object detection, segmentation, tracking, multi-view and egocentric vision, 3D and spatial reasoning, pose estimation, calibration, localisation, sensor fusion, or real-time vision systems. - Education: A PhD in machine learning, computer vision, robotics, computer science or a related field is valuable but not required. An equivalent record of original model work, technical leadership, and real-system delivery is sufficient. We care more about what you personally designed, trained, tested, and deployed than about a specific degree or number of years. NICE-TO-HAVE: - Technical expertise: Experience with VLA or robotic foundation models, action generation, diffusion or flow-matching policies, imitation learning, reinforcement learning, world models, robotic manipulation, cross-embodiment training, sim-to-real transfer, distributed training, ROS 2, or safety-critical systems. - Additional experience: Research publications, open-source contributions, early-stage company experience, or direct collaboration with technical customers and research partners.   WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Almaty, Kazakhstan Workplace: hybrid We’re looking for a Safety Governance Analyst to help make safety at inDrive measurable, consistent and auditable. You’ll map how safety processes really work across markets, test them through structured sampling and QA, and turn findings into clear standards, fixes and reporting. It’s a hands-on role for someone who is equally comfortable writing a SQL query, drawing a process map and drafting a procedure. Key Responsibilities Map end-to-end safety processes, including incident intake, case handling, escalations and driver/rider actions, using BPMN or Lean methods, and identify gaps, risks and inefficiencies Design and run QA and sampling reviews of safety cases and controls: define sample sizes, review criteria and scoring Log findings, agree remediation actions with process owners, and track them to closure Maintain the risk-acceptance register: log each entry, confirm the named acceptor and rationale, record sunset and review dates, and track entries falling due for review Build and maintain the safety governance report pack using AI/automation tools, independently and on a regular cadence Check safety data quality and flag inconsistencies in how incidents are classified and counted Run root-cause analysis on safety trends and recurring findings, and propose practical process improvements Skills, Knowledge & Expertise 3+ years in safety operations, trust & safety quality assurance or process excellence Practical knowledge of sampling and QA methodology, plus findings and remediation tracking Strong SQL skills and experience with a BI tool (Tableau, Data Studio / Looker Studio or similar); you can build a full report pack on your own Hands-on AI mastery with Claude: you can quickly build clear visualisations and storylines that explain complex safety risks in simple terms to any audience Experience with process notation (BPMN or other) Ability to write clear, structured standards and procedures A structured, detail-oriented approach and confidence presenting findings to stakeholders Strong interpersonal skills: you stay calm and attentive in difficult conversations, can deliver unwelcome QA findings to process owners, and persuade teams outside your authority to act on them Fluent English Strong plus: Experience in ride-hailing, mobility, delivery or another business with offline safety risks A certificate in data analytics 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 a Safety Governance Manager to build and own how safety is governed across inDrive’s platform. You’ll set the framework, metrics and reporting that turn safety work into measurable outcomes for riders, drivers and couriers in 47 countries. You’ll work closely with Product, Operations, Legal and Data teams, and report safety performance up to senior leadership and the board. Key Responsibilities Design and launch inDrive’s safety governance framework from the ground up: policies, standards, risk register, controls and review cadence. Verification and reporting. Verify that safety processes and product features work as described. Verify the integrity of safety metrics: review against the approved methodology and independently re-sample incidents with direct access to the underlying data. Return gaps to control owners for remediation, and deliver findings to the senior management through a set reporting cycle. Design the methodology and format for the verification and reporting Safety decision tracking. Design and maintain the risk-acceptance register. Assess each entry against the safety risk appetite statement and report the state of the register to senior management. Safety spend baseline and gap review. Review the safety spend baseline and the costing methodology. What this role does not do. Safety Governance does not own, operate or deliver safety controls; does not set the taxonomy, classification, methodology or other business standards it verifies against; does not accept safety risk; and does not decide how safety controls are resourced. Skills, Knowledge & Expertise 5+ years in trust & safety, safety operations, risk assurance or compliance programme management Experience in ride-hailing, mobility, delivery or another business with offline safety risks with a strong governance background (inc. risk management frameworks and board-level reporting) Data literacy: you can specify metrics, challenge a dashboard and interpret a sampling result Hands-on AI fluency (Claude or similar): you can quickly build clear visualisations and storylines that explain complex safety risks in simple terms to any audience Enough legal literacy to work effectively with counsel (a law degree is not required) Strong stakeholder management across Product, Operations, Legal and Data teams in a global environment Strong interpersonal skills: you stay calm and attentive in difficult conversations, can deliver unwelcome QA findings to process owners, and persuade teams outside your authority to act on them Fluent English Strong plus: Experience in ride-hailing, mobility, delivery or another business with offline safety risks Hands-on experience designing or managing an incident taxonomy TSPA (Trust & Safety Professional Association) membership A certificate in data analytics 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. Annual salary starting from 67 600 EUR Gross. Final benefits may vary depending on the location.

Location: Москва Наша команда разрабатывает SDK, встраивающийся в мобильные приложения банка и ДЗО, предоставляющий возможность отвечать на вопросы и решать задачи пользователя посредством большой языковой модели GigaChat. Работая с нами, вы станете частью команды, которая создаёт инновационные продукты и сервисы, открывающие новые горизонты для миллионов клиентов и помогающие им решать ежедневные задачи максимально эффективно. Обязанности * опыт работы в релевантной должности от 4х лет * создавать компоненты, адаптируемые под целевое приложение * разрабатывать новую функциональность SDK: историю чатов, контекстуальные точки входа * дорабатывать и развивать текущую функциональность: отправку файлов, голосовое взаимодействие, интеграцию с поиском * решать системные задачи, такие, например, как перевод сетевого слоя SDK из WebView в натив Требования * мы работаем в быстро изменяющейся AI индустрии, поэтому важна твоя готовность работать с большим количеством неопределенности * уверенное владение Kotlin и Coroutines * знание Jetpack Compose и Android SDK в целом * умение применять паттерны проектирования, понимание инверсии зависимостей * знание REST API, работа с протоколами HTTPS, WebSocket. Будет плюсом: * опыт разработки приложений end to end * понимание принципов Offline First * опыт разработки чата * опыт работы с WebView и умение работать с инструментами отладки WebView * опыт разработки библиотек и проектирования API Условия * гибридный график работы (офис рядом с метро Кутузовская), * годовую премию, * занятия спортом в корпоративном зале и зоны отдыха, * более 400 курсов СберУниверситета для личного и карьерного роста, * регулярные встречи профессионалов и активное сообщество специалистов DS, * расширенную медицинскую страховку, льготы на страхование семьи и участие в корпоративной пенсии, * сниженную ставку по ипотеке до трети ключевого показателя Центробанка, * подписку СберПрайм с совместным использованием на троих членов семьи, * вознаграждения за рекомендации своих знакомых.

Location: Москва Workplace: Офисный Мы — отдел экспериментальных технологий в AI VK, который решает широкий спектр ML- и DL-задач. Наша команда анализирует, как наши разработки можно переиспользовать и где применить, а затем масштабировать. Задачи Развивать компоненты AI-ассистента для VK Видео: понимание намерения, удержание контекста диалога, выбор стратегии и маршрутизация инструментов Улучшать генерацию кандидатов, semantic retrieval и reranking для поиска и персонализированных рекомендаций Работать с гибридным поиском: эмбеддинги, текстовые и структурные фильтры, поисковые API, рекомендательные модели и явные критерии пользователя Оптимизировать candidate budget и смешивание кандидатов из разных источников Обучать и дообучать модели для отдельных компонентов системы: LLM-like, reranker, query rewriting, relevance-модели Собирать и улучшать обучающие и тестовые датасеты: реальные и синтетические запросы, сложные негативные примеры, long-tail-сценарии и размеченные диалоги Создавать и поддерживать golden datasets, human-aligned evaluation и автоматические проверки качества; калибровать auto-eval по человеческой оценке Анализировать деградации, формулировать гипотезы и проверять их в воспроизводимых экспериментах Оценивать модели не только по общей метрике, но и по отдельным сценариям, категориям запросов, релевантности, разнообразию, безопасности и качеству диалога Оптимизировать latency, стоимость и использование вычислительных ресурсов при обучении и инференсе Готовить компоненты к промышленной эксплуатации: интеграция, нагрузочное тестирование, мониторинг, обработка ошибок и контроль регрессий Участвовать в offline- и online-экспериментах, подготовке A/B-тестов и интерпретации продуктовых метрик Проводить code review, документировать эксперименты и участвовать в обсуждении архитектуры и исследовательских результатов Требования Сильная теоретическая база и опыт работы в рекомендательных системах, информационном поиске, NLP/LLM; готовность работать на их пересечении Понимание устройства retrieval и ranking: embeddings, candidate generation, negative sampling, cross-encoders, reranking Знание основных offline-метрик поиска и рекомендаций: Recall@K, Precision@K, NDCG, MRR и их ограничений Опыт обучения, валидации и внедрения ML-моделей; доведённые до production либо production-like среды самостоятельно разработанные компоненты Навыки постановки воспроизводимых экспериментов, анализа ошибок и статистической интерпретации результатов Понимание жизненного цикла ML-системы: данные, обучение, inference, мониторинг, деградации и переобучение Опыт работы с большими объёмами данных и пайплайнами обработки; YT, Spark или аналогичные инструменты Базовые навыки Linux, Git, контейнеризации и работы с сервисами Будет плюсом Опыт создания LLM-приложений: tool calling, agentic workflows, RAG, structured generation Дообучение LLM или encoder-моделей: SFT, LoRA/adapters, RL Построение lexical, semantic или hybrid retrieval LLM-as-a-judge, human evaluation, построение golden datasets и калибровка автоматических оценок Оптимизация GPU-инференса, batching, quantization, model serving Опыт с распределённым обучением и промышленной ML-инфраструктурой Практика A/B-тестирования рекомендательных или поисковых моделей Мультимодальные модели, VLM, понимание видео или рекомендательные системы для медиаконтента Наличие публикаций по тематике LLM, NLP, multimodal models

Location: Москва Workplace: В офисе О компании Расширяем команду отдела продаж и приглашаем коллегу на роль "Ведущий менеджер по развитию продаж рекламы" в команду МТС LIVE Обязанности Продажи рекламных возможностей билетного оператора МТС Лайв внутренним клиентам - организаторам мероприятий Разработка новых инструментов продвижения на собственных витринах Разработка новых рекламных инструментов в диджитал, охватной и offline-рекламе Разработка и создание комплексных коммерческих предложений для клиентов Защита ранее разработанных коммерческих предложений Участие в переговорах и встречах по запуску РК с клиентами Ведение клиентов от подготовки предложения до запуска рекламной кампании Требования Опыт работы в продажaх рекламы от 1 года, предпочтительно в e-commerce Знания и умение оперировать показателями аналитики рекламных инструментов Опыт формирования медиакита Опыт внедрения новых рекламных инструментов Навыки планирования бюджета доходов/расходов по продажами рекламы Навыки формирования ТЗ на доработки витрин/отчетнотсти Опыт взаимодействия с подрядчиками рекламного рынка: Рекламные Агентства полного цикла, Типографии Понимание специфики рынка e-commerce, его особенностей, процессов и терминологии Опыт и желание лидирования новых проектов, включающих взаимодействие с несколькими департаментами внутри компании Уверенное владение PowerPoint, Excel, желательно графические редакторы Условия Оформление согласно ТК РФ Заработная плата обсуждается по итогам собеседования Современный офис в центре Москвы (м. Цветной бульвар/Трубная) График работы 5/2 (офисный формат работы, возможность дней для удаленного формата, по согласованию с руководителей) Гибкое начало и окончание рабочего дня ДМС с первого месяца работы, включая стоматологию. А еще оплачиваем 50% стоимости полиса ДМС для родственников Страхование от несчастных случаев с 1 месяца работы Материальная помощь в сложных жизненных ситуациях Обучение за счет Компании Корпоративные скидки от партнеров Бесплатная мобильная связь Руководители и коллеги, всегда готовые поддержать и помочь Возможность профессионального и карьерного роста

- Исследование, проектирование и разработка архитектур легковесных ИИ-моделей детекции и сегментации дефектов для работы в offline-режиме на edge-устройствах. - Разработка алгоритмов предобработки изображений (кастомные фильтры для устранения бликов, артефактов освещения и шумов на металле).

Location: Brussels, Belgium Workplace: hybrid Location: Any MSF office* Contract: Permanent contract at 100% Starting date: 01.12.2026 Deadline to apply: The position will close once a suitable candidate has been selected Compensation and Benefits: MSF practice is to offer the compensation and benefits package in line with the MSF entity offering the contract *By default, the successful candidate will be offered a contract in the MSF office, able to issue a contract, of their country of residence at the time of application. If no MSF office exists in their country of residence, the successful candidate will be expected to relocate to a country where an MSF office can issue a contract, provided the local legislation allows for that. At MSF, we are committed to an inclusive culture that encourages and supports the diverse voices of our employees. We welcome applications from individuals of all genders, ages, sexual orientations, nationalities, races, religions, beliefs, ability status, and all other diversity characteristics. MSF is committed to preventing abuse, inappropriate behaviour, lack of integrity and financial misconduct in its work and care spaces. The successful candidate will be expected to comply with the organisation’s safeguarding policies and standards of professional behaviour. We are committed to removing barriers for people with specific accessibility needs. If you need an adjustment to the recruitment process to be considered for the role, please let us know from the beginning of the selection process. I. MSF International Médecins Sans Frontières (MSF) is an international, independent, medical humanitarian organisation that delivers emergency aid to people affected by armed conflict, epidemics, healthcare exclusion and natural disasters. MSF offers assistance to people based only on need and irrespective of race, religion, gender or political affiliation. MSF International is the legal entity that binds MSF’s 24 sections, 28 associations and 19 branch offices together. Registered in Switzerland, MSF International provides coordination, information and support to the MSF Movement, as well as implements international projects and initiatives as requested. II. POSITION BACKGROUND Coordination and Source of Product Information (SPINCO) was created to maintain consistency in the choice of medical and non-medical articles between MSF sections in order to improve MSF interventions, while considering field realities. SPINCO is the driver for effective collaboration across the movement to deliver a central source of trusted product information that enables continuous process improvements. SPINCO contributes to MSF’s social mission by enabling improvements in field operations through the provision of product information to all layers of the organization. This enables product quality and visibility for better quality of care, enables assortment management, improvement in supply chain performance and increases overall interoperability whilst reducing duplication of effort. SPINCO’s core role is coordinating the expression of the demand of articles (medical and non-medical) and ensuring it is properly translated for supply whose role is to fulfil that demand. In 2018, UniQuality was implemented as the unique central quality assurance database of MSF, containing the quality assured drugs, medical devices and specialised food validated for use in MSF projects. It is used by the MSF International Pharmacist Network, International Specialised Foods Network, and International Medical Devices/In-vitro Diagnostics Network, and Supply Centres to allow access to the most up-to-date validated product-manufacturer information. In 2022, the UniMed project was launched to connect UniQuality to the supply centres’ ERP systems and automate the dissemination of the information regarding medicines and specialized food, to ensure the accuracy and consistency of quality review information. This position will support the completion of UniQuality for Medical Devices and IVDs in preparation of the linkage of both systems for this category of products as well. In 2024 the Medical Device Repository, a SharePoint library for regulatory, quality and technical documents, went live to facilitate importation procedures with a direct access for field teams, and to keep product validation documentation after assessment by IO and ESC QA referents. In 2025, the NexSpin project was launched to replace the existing solutions including UniQuality and the MD repository by a new Product Information Management System aiming at improving operational efficiency, user experience and user interface. This requires cleaning of the existing solutions, providing input to the NexSpin team as key users and being involved in the implementation phase scheduled in 2027. Medical Device UniQuality & Unidata Product Information Specialist open-end position (100%). III. PLACE IN THE ORGANISATION The person reports to the SPINCO Product Information Specialists Coordinator with a functional reporting line to the Deputy Quality Assurance coordinator for Medical Devices. The person will closely coordinate with the Data-Owners in the International QA MD Coordination team and the European Supply Centres. IV. OBJECTIVES OF THE POSITION This position is focused on Medical Devices (MD). The objective of the position is to ensure that information related to Entities and Quality Review in UniQuality and the MD Repository is complete, accurate and available for the relevant MSF stakeholders. By guaranteeing the compliance with Quality Assurance processes, the Uniquality Data Steward’s role is to safeguard the quality of information in UniQuality and the MD repository, as well as the consistency between both tools. They will act as primary point of contact for all stakeholders in case of questions about rules or non-conformity of information contained in UniQuality. They will develop a plan to gradually introduce a data quality and reporting plan to ensure that trust is maintained. The Unidata Product Information Specialist role contributes to MSF social mission by ensuring the availability of trusted, standardized, and high-quality product information. This role supports field operations, supply chain performance, and interoperability through centralized data stewardship, product portfolio management, and collaboration with diverse stakeholders. V. MAIN RESPONSIBILITIES A. UniQuality Data Steward 1. Management of Entities in UniQuality: Currently close to 1300 MD international entities in UQ Create, validate and update MD entities according to the relevant SOP, more specifically: Create new entities upon request of ESCs QA referents and Spinco data stewards (creation of a new article code), by verifying the availability of documents in the MD Repository for manufacturers not existing in UQ Support the update/cleaning of the ESC database of entities. Approve the entities for MD International purchase by checking for completeness of data in relevant public database, e.g. Eudamed, FDA registration, Conformity Assessment Bodies database for ISO certificates Update the entities (name / address) according to new supplier information received from ESC and by regularly checking public database 2. Management of ISO certificates Close to 1000 ISO certificates in the MD repository Search for online information: manufacturer’s website, Conformity Assessment Bodies and Accreditation Bodies database Ensure that information related to ISO certificates in UQ and in the MD Repository are updated and consistent, especially for entities associated to quality reviews. Request updated documentation to the ESC referents or regulatory assistants. Update the list of the certification bodies in UQ and the related information: NB number, accreditation, link to online directories for certificates verification 3. MD Repository Currently around 9000 documents in total, will grow as quality reviews are completed Ensure that the rules set for the uploading and tagging of regulatory and quality documentation in the MD repository are followed by all stakeholders, i.e., IO MD QA Coordination, supply centers QA referents and regulatory assistants, RA Pharma, and field users. Check regularly recently uploaded documents: naming of file is correct, tagging is completed, certificates information in UQ (ISO and EU/CE certificate) is updated, duplicates are removed Assist the end-users with practical use of the MD Repository and report issues to the helpdesk if needed. 4. Eudamed Follow up the use of the different modules in Eudamed: changes of activities, new documentation and information available. Inform the QA referents of changes. Train the different groups (ESC QA referents, intersection pharmacists) in the practical use of Eudamed. Liaise with the Spinco development team for the possibilities to link with Eudamed in Uniquality 5. General UniQuality / MD Repository Propose improvements and updates of SOP for UniQuality and the MD Repository as necessary, in collaboration with the product owners and in agreement with the main stakeholders Propose an action plan to review and improve the quality of information aligned with the needs and work capacity of the stakeholders. Implement an annual report/control on data quality of UniQuality and the MD repository by defining the quality criteria and setting the KPI in collaboration with the MD QA coordination Train new UniQuality / MD Repository users by developing e-learning tools, and organizing training sessions in collaboration with the UQ product owner B. Unidata Product Information specialist 1. Product Information Management Monitor, evaluate, and process requests for new, modified, or removed products in alignment with MSF guidelines, protocols and standards. Consolidate and validate information on product description, quality, pricing, field testing, and maintenance requirements for approval by the Medical Directors' platform. Ensure product availability and suitability for field use by collaborating with QA teams, buyers, and regional hubs. Owns the data product lifecycle and technical specifications Ensures the product meets user needs and use cases Prioritises improvements and manages changes over time 2. Harmonization and Interoperability Collaborate with intersectional platforms, supply centres and field operations to standardize products across MSF operations. Facilitate resource sharing and intersectional field operations by ensuring product harmonization. Promote responsible use of product data to balance efficiency, cost, and humanitarian mission. 3. Data Stewardship Ensure and maintain the high quality of product information in terms of accuracy, validity, consistency, completeness, uniqueness and accessibility of product information in the UniData tool, MSF central article database. Ensure UniData serves as the single source of truth for downstream systems (e.g., ERP, UniQuality, order tools). Govern the central database and ensure compliance with regulatory standards (e.g., EU norms, ISO standards, IATA transport regulations). Promote consistency and usability by maintaining aligned definitions (Knowledge database, KPIs) and making data fit for decision-making. Support continuous improvement by identifying data issues, proposing enhancements, and acting as a bridge between technical team and IT 4. Data ownership: accessibility and visibility Responsible and accountable for the accessibility and visibility of product information Publish product information on accessible platforms (web, intranet, offline tools) for global MSF staff. Act as the focal point for central database governance and user support. 5. Process Design and Improvement Responsible and accountable for data governance: how product information is defined, created and used Design, implement, and enhance processes related to data requirements, product codification, and multilingual labelling. Pushing data governance by setting the direction and objectives Actively promoting improved data governance practices (RACI). Ensure product information data supports reliable operational & strategic decision-making Publish annual summaries of medical product changes and updates to MSF catalogues. Publish monthly reports on medial product changes for the ESC referents and medical referents of the OC/OD’s Develop policies, guidelines, and training materials for approximately 1,700 database users. 6. Collaboration and Stakeholder Engagement Work closely with MSF field staff, headquarters, Quality Assurance teams, tactical buyers and intersectional platforms to ensure product standardization and quality of product information. Participate in international projects with NGOs and UN sectors, such as emergency health kits and medical device nomenclature initiatives. VI. SAFEGUARDING RESPONSIBILITIES OF THE ROLE The incumbent commits to contribute to a safe, supportive, inclusive, equitable, diverse, respectful, and healthy workplace, free from abuse and other misconduct.  They will not engage in any form of abuse including those detailed in MSF Typologies of Abuse and when an employee suspects or observes abuse, they will report it to protect others. Master’s degree in scientific, engineering, pharmacy or paramedical sciences Detail-oriented, meticulous and organized for data entry/modification in database is essential Computer & analytical skills, including MS Excel are essential Knowlegde of Medical Devices regulatory environment (MDR/IVDR) and ISO standards is a plus Proficiency in English (both speaking and writing) and knowledge of French MSF field or Supply experience in a medical position is an asset Fast learner, able to adapt quickly to a changing environment Customer oriented, resilient, with good people and communication skills Self-motivated, with an interest in problem solving Excellent time management skills, with the ability to prioritise and multi-task depending on the needs. Technical writing capacities. Only shortlisted candidates will be contacted. At MSF, we are committed to an inclusive culture that encourages and supports the diverse voices of our employees. We welcome applications from individuals of all genders, ages, sexual orientations, nationalities, races, religions, beliefs, ability status, and all other diversity characteristics. MSF is committed to preventing abuse, inappropriate behaviour, lack of integrity and financial misconduct in its work and care spaces. MSF expects all staff to share this commitment and promote an environment where abuse and misconduct is not tolerated. We are committed to removing barriers for people with specific accessibility needs. If you need an adjustment to the recruitment process to be considered for the role, please let us know from the beginning of the selection process. Note: All offers of employment will be subject to reference checks and to appropriate screening checks. By submitting an application, the job applicant confirms his/her/their understanding of these recruitment procedures.

Location: Intellias Meet your recruiter Yustyna Vozna yustyna.vozna@intellias.com https://www.linkedin.com... Vacancy details Software Engineering JavaScript Engineer (React) Senior Bulgaria, Croatia, Poland Remote APPLY NOW REFER A FRIEND Make retail great again through the power of technology! Intellias helps retailers provide consistent and customer-centric shopping experiences across all channels with disruptive retail tech solutions. Get on board and make your own contribution to the industry! What project we have for you With great experience come great projects. Just imagine: you can develop a product that should completely change the business of one of the world’s largest companies! Our client is an innovative global company from the Fortune 500. Consumer Goods Producer and Retailer with headquarters in Switzerland that sells its products in 130 countries. Intellias mission is to support its strategy and efforts in the Digital and eCommerce space. A newly conceptualized Digital Eco System is comprised of a set of capabilities including an online shop & website, linking online & offline, customization & personalization, engagement & membership, digital products & services. What you will do Creating technical vision & documentation Participate in architecture and design efforts Code review, code optimization Technical tasks implementation, design, refactoring Collaborate with other engineering teams to resolve dependencies and deliver high-quality software on time, etc. What you need for this Own the design and delivery of reliable frontend features across the Next.js application and shared packages. Collaborate closely with product, design, backend, and QA teams while helping the team make technical decisions. Requirements Senior-level experience delivering production web applications, with 7+ years in frontend development. Strong experience with React, TypeScript, and modern Next.js, including App Router patterns and server/client rendering. Ability to design maintainable components and shared packages/APIs within a large monorepo. Experience integrating frontend applications with GraphQL and REST APIs, including generated types, loading and error states, and evolving backend contracts. Proficiency in responsive and accessible UI development using CSS Modules/SCSS, with the ability to work within an existing design system and follow design token conventions. Experience with frontend state management, such as Redux and React Context. Solid understanding of testing and quality practices, including Jest or Vitest, Testing Library, Storybook, and browser testing frameworks. Familiarity with monorepo tooling and CI quality gates, including linting, PR workflows, type checks, and builds. Strong debugging, code review, and written communication skills. Ability to take ownership of features through implementation, testing, release, and production follow-up. Experience using modern AI development tools to improve productivity, such as GitHub Copilot, Codex, or Claude Code. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills English HTML/CSS React

Location: Remote - Ontario, Canada (DNU) Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Staff Machine Learning Engineer on Twilio’s AI/ML Platform team. About the job We are actively recruiting for this role to fill an existing vacancy. This position is needed to build the foundational AI/ML capabilities and common platform tooling that power intelligent engagement experiences across Twilio. You will influence the design and evolution of our company-wide ML/AI Ops foundation, ensuring every AI capability incorporates rigorous offline and online evals to maintain exceptionally high quality. You will drive improvements to managing LLM workloads across the company, while ensuring easy and compliant access to data for AI/ML exploration and product development. This role requires a builder mindset to bridge theoretical research, production-grade experimentation, and scalable, enterprise-quality software. Responsibilities In this role, you’ll: Conduct deep-dive research into and implement state-of-the-art LLM inference and orchestration. Identify opportunities to leverage small language via fine-tuning/distillation. Build ML systems that hold up at Twilio scale. Set standards and tooling for building evals across a range of AI/ML capabilities. Rapidly acquire new technical skills and knowledge in a fast-paced, high-delivery environment. Proactively leverage and integrate the latest AI development stacks to bypass boilerplate engineering and focus on core differentiation. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: 8+ years applied ML/AI experience with a track record of owning technically ambitious systems end to end rather than contributing to someone else's design. Comfort operating in a 0-to-1 setting with ambiguous requirements and a strong bias for action. Proficiency in Python programming language. Experience building cloud-based services on AWS, GCP, or Azure, with high-volume data, streaming or real-time inference paths, and a range of data stores. Strong fundamentals of statistical machine learning algorithms, transformer models, LLMs. Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics for non-deterministic AI features at scale. Strong communication skills and highly effective collaborator who works well with teammates. Familiarity with AI-assisted development tools (e.g., Claude, Codex, GitHub Copilot, Cursor, etc.). Desired: Prior experience building evals for autonomous agents and large language models. Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context/consistency. Prior experience working in a globally distributed team. Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research. Location This role will be remote and based in Ontario, British Columbia or Alberta, Canada. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off. The estimated pay ranges for this role are as follows: $160,320 - $200,400 Target Bonus Percentage 12.5% The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: Berlin, Germany The Publishing team in EMEA provides many direct-to-player publishing functions, such as content operations, marketing communications, strategy development, competitive experience, events, and full-funnel strategy. The team also establishes and maintains internal services such as platforms, vendor management, project management, RFPs, and working with player insights. The team is dedicated to providing platforms for authentic local interactions and channel experiences for players and Rioters, both online and offline. The team also ensures that our pan-EMEA content will reach players through the right channel, collaborating closely with EMEA and country-based publishing teams. Reporting to the Regional Community Lead, EMEA, you will be based in Berlin (Germany). As Social Media Strategist II, EMEA , you will work on League of Legends, collaborating with the EMEA Community, Brand, Esports, Local Publishing Teams, Global Publishing, and partners to deliver impactful campaigns, content, and initiatives across all our products and social channels, including LEC. You will be responsible for driving the ongoing success and sustainable strategy for our regional and LEC socials, and positioning Riot for success in the years ahead, working closely with our partner agencies. You will work closely with the Regional Community Lead, EMEA, to create campaigns that resonate with our players and ensure these campaigns deliver on their objectives. You will also bring a high level of social media expertise, supporting local publishing teams in their channel efforts to target different audiences and contributing from a social operations perspective. This is a 12 month contract role starting in January 2027 and based onsite in Berlin on a hybrid basis. Responsibilities: Partner with EMEA Publishing teams to provide social media expertise, share best practices, and inform social-first approaches across the broader League of Legends product portfolio Contribute to the development of EMEA-wide Publishing campaigns by bringing a social media perspective to campaign strategy, content planning, and audience engagement Identify opportunities to connect esports initiatives with broader Publishing priorities, ensuring social strategies contribute to a cohesive experience for players and fans across the ecosystem Collaborate with a partner agency to develop and refine channel strategies for LEC, ensuring alignment with Riot's overarching goals and objectives Define and track key performance indicators (KPIs) for social media performance, delivering regular reports and actionable insights to internal stakeholders Support the Social Media strategy and coverage on-site for LEC events & roadtrips Partner with the EMEA Comms and Esports Team to ideate and produce innovative content that resonates with esports fans Partner with community teams to amplify player and fan stories, fostering deeper connections within the LEC ecosystems and identify how to reach different target audiences Serve as the primary point of contact (POC) for social leads from the LEC teams, collaborating to build campaigns that support key esports milestones Monitor social trends, audience sentiment, and competitive benchmarks to identify opportunities for growth and optimization Collaborate with global Riot teams to ensure EMEA social initiatives are aligned with global esports campaigns Required Qualifications: 5+ years of experience in social channel management at an agency or in-house in the video game, technology, or entertainment industry Global or regional experience working across multiple countries/markets Knowledge of regional differences, different target audiences, market sensitivities, cultural curiosity and understanding, differences in localization Experience implementing successful communications campaigns with passionate audiences Experience growing content pipelines (in-house and external/agency) Fluent in written and verbal English. Desired Qualifications: Experience in a multinational environment, particularly in the EMEA region. Besides English, you are fluent in any additional EMEA-relevant language  (French, German, Spanish, Turkish, Arabic, or Russian) 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! At Riot Games, we put players first . That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.