Вакансии

- Покрывать критические процессы: запуск задач, авторизацию, публикацию, получение результатов, повторные попытки и обработку ошибок. - Выстраивать автоматизированные smoke- и regression-проверки после изменений в коде.

Location: London Workplace: OnSite Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. Checkout.com http://Checkout.com is looking for an ambitious Senior Engineering Manager to join our Disputes team. Our mission is to build the tools, services, and models that help merchants manage and win disputes at scale - reducing the cost and operational burden of chargebacks while protecting revenue for our merchants and our business. Disputes sit at the intersection of merchant-facing products, complex scheme and regulatory processes, and data-driven decisioning. Our team owns the full stack, anchored by a .NET back end that manages the dispute lifecycle and integrates with card schemes, alongside the front-end experiences merchants use to track and respond to disputes and the machine learning models that predict outcomes and recommend the best action on every case. We're building for scale, and that scale brings ambiguity, shifting priorities, and the occasional setback - so we're looking for a resilient leader who has built and sustained high-performing teams, learned from failure, and come back stronger. Above all, you'll be someone who drives predictable delivery and operational efficiency: shipping consistently, running systems reliably, and continuously improving how the team works. The ideal candidate has operated across both enterprise and scale-up environments and has a proven track record of driving growth within large, complex, regulated organisations. Key Responsibilities - Lead a team centred on a .NET back end, with front-end and machine learning components, helping engineers establish and validate their understanding of technical architecture and design end-user-centric systems and tools. - Own predictable, high-velocity delivery — establishing healthy engineering practices, sensible estimation, and a smooth path from idea to production so the team ships consistently and sustainably. - Drive operational efficiency and reliability by automating processes — including monitoring and alerting — meeting SLAs/SLOs, reducing operational cost, and minimising toil to keep the team focused on high-value work rather t - Continuously improve delivery and operational metrics (e.g. cycle time, deployment frequency, change failure rate, and incident response), using data to identify bottlenecks and raises the bar over time. - Manage team engineers across various seniority levels and disciplines while staying hands-on when needed. Cultivate an inclusive environment where every team member feels they belong, and mentors them in both their career development and interpersonal skills. Make a good team great, and keep it great.. - Oversee quarterly execution of roadmap delivery, ensuring the team stays focused on the right priorities and manages efficiently through dependencies and cross-functional hurdles. - Collaborate across Engineering, Product, and Operations to deliver solutions for merchant and internal dispute use cases. - Build and strengthen relationships with engineers, managers, and people leads across multiple teams. - Operating in a highly regulated financial space, ensure compliance with a range of control frameworks — from internal stakeholders such as InfoSec and Internal - Audit, to external auditors, card schemes, and regulators. - Oversee the responsible use of machine learning and AI in dispute decisioning, leading the team to develop the infrastructure, tooling, and governance required to run models safely and at scale in production. About You - A resilient leader who has learned from setbacks and failures and consistently comes back stronger, keeping teams steady and delivering through periods of change and ambiguity. - You thrive on pace. You're energised by a high-growth environment, comfortable making decisions with imperfect information, and you keep the team moving and shipping when priorities shift under you. - A proven track record of driving predictable delivery and operational efficiency — improving throughput, reliability, and the team's cost of operation, and using metrics to back it up. - Proven experience building, growing, and sustaining high-performing engineering teams over time — not just standing them up. - Experience across both enterprise and scale-up environments, with a demonstrated track record of driving growth and delivery within large, complex, regulated organisations. - A strong back-end engineering background, ideally in .NET / C#, leading teams building scalable, event-driven services and APIs. Comfortable also overseeing front-end and machine learning work, able to earn credibility and make sound trade-offs across disciplines even where you aren't the deepest expert. - Able to partner with Product Management to assess technical feasibility, provide capacity estimates, and balance new features against architectural health. - Excellent time management and proactive problem-solving skills. Technologies we work with - Back end (primary): .NET / C#, REST APIs, event-driven and microservice architectures. - Front end: React, TypeScript. - Machine learning: Python, model training and serving, and the infrastructure to run models in production. - Data & platform: SQL, plus experience designing batch and stream data-processing systems. - Cloud & tooling: AWS and/or GCP, Docker, Terraform, and observability tooling such as Datadog. - Knowledge of Kubernetes, Kafka, and CI/CD pipelines is highly beneficial. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

• Проектировать и создавать ИИ-инструменты для автоматического производства дизайн-макетов.

TLDR: Ищем Applied AI Engineer (Middle+) для разработки и тестирования AI-систем, улучшения качества и автоматизации внутренних процессов. - 3+ года опыта в разработке AI/LLM-систем.

Work alongside the sales team to introduce CockroachDB to our potential customers. As a trusted advisor, you will help educate prospects on the unique capabilities of CockroachDB and design solutions to meet a wide variety of challenges.

What You’ll Do: Lead, coach, and develop a team of engineers building Reddit’s Knowledge Graph Platform;

Design and operate a fleet of Kubernetes (EKS) clusters across production, staging, and ephemeral environments, ensuring reliability and high availability. Evolve AWS infrastructure and network architecture (VPCs, subnets, IAM, account structure) to support scalable, multi-team workloads.

Location: Remote; Europe Workplace: Remote About us We're building an open, safe and sustainable marketplace for the gamers of today and tomorrow. Our marketplace supports more than 20 m+ active users (and growing fast!), provides a level of trust, safety and market accessibility unparalleled to none. We're proud of what we've accomplished in such a short time and look forward to sharing this journey with you. Join us as we continue to scale, diversify our portfolio, and grow with the evolving community of gamers. About the team We are a cross-functional team of 5-10 people with designers, backend, frontend, mobile, and data engineers. They are supported by a platform engineering team. We move fast, experiment, learn a lot, and build new products for our growing base of 10+ million active users. Responsibilities - Utilize your expertise to design, develop, test, deploy, maintain, and improve our software. - Produce code that reads like poetry and takes full ownership of your work: builds, ships, and maintains your codebase to the highest standards as we scale. - Raise the bar of our entire technology stack: detect and act upon inefficiencies in architecture, codebase design, and/or implementations with O(n!) complexity. - Develop new features while in product discovery, bring innovations to vendor tooling, and launch solutions that will affect user growth, service quality, and sales metrics. - Contribute to the development of one of our flagship products: Digital, Physical, and/or Payments & Risk. - Effectively partner with product managers, fellow engineers, designers, and the entire cross-functional product team working towards top user value. - Deliver measurable impact, track outcomes, and bring continuous improvements to dramatically boost our team's impact. Requirements - 3+ years of experience developing with React; preferably with TypeScript. - Experience in communicating with cross-functional and technical teams, as well as product management to collect requirements, describe software product features, technical designs, and engineering/product strategy. - Basic understanding of GraphQL, Express, CSS Modules, SASS. - Knowledge of AI coding tools: Claude, OpenCode, Cursor and Codex. - Background in building complex user-facing features, and writing well-structured, efficient, and maintainable code. Nice to have - Basic knowledge of Redis. Salary: EUR 55.000-70.000 a year Salary ranges may vary. We're seeking candidates with varied experience levels; from individual contributors to functional leaders in this space. We're an international team and our business language of choice is English. Good English level is required, proficiency is preferred. To find out about how we handle your personal data, make sure to check out our Candidate Privacy Notice: https://www.eneba.com/candidate-privacy-notice What it's like to work at Eneba - Opportunity to join our Employee Stock Options program. - Opportunity to help scale a unique product. - Various bonus systems: performance-based, referral, additional paid leave, personal learning budget. - Paid volunteering opportunities. - Work location of your choice: office, remote, opportunity to work and travel. - Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes.

— проходить тест-кейсы (сценарии); — воспроизводить ошибки (bugs) и верифицировать исправления (fixes);

Чем предстоит заниматься: собирать программные прототипы и эмулировать устройства на ПК для тестирования наших продуктов; разрабатывать утилиты, скрипты и мини-приложения для автоматизации рутины, а еще тестировать интеграции;

Location: London, United Kingdom Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. About the role We are looking for an Engineering Manager to lead Codeless, our internal Server-Driven UI (SDUI) platform team. In this role, you will lead a cross-functional team bridging mobile/web frontend engineering and core platform backend systems. While this role is deeply rooted in modern UI architecture, its mission goes beyond standard UI development: Codeless empowers product teams across the organization to ship dynamic, native UI experiences dynamically from the backend—eliminating app store release bottlenecks, dramatically accelerating feature iteration, and establishing a unified UI schema across iOS, Android, and Web. What you’ll be doing This is a role with broad impact, from hands-on technical guidance to championing web and mobile accessibility across the company. We're looking for a leader who excels at fostering collaboration and can confidently guide a concept from initial idea to robust implementation. Day-to-day in this role you’ll: Team Leadership & Strategy: Build, mentor, and scale an engineering team responsible for our core Server-Driven UI platform ("Codeless"). Foster an inclusive, high-ownership engineering culture. Platform Architecture & Evolution: Oversee the design and evolution of dynamic layout engines, declarative UI schemas, and client rendering frameworks across iOS, Android, and Web. Developer Velocity & Platform Adoption: Partner with product feature teams to drive internal adoption of Codeless. Ensure the platform provides exceptional Developer Experience, clear tooling, robust design system integration, and seamless debugging workflows. Technical Execution & Quality: Set high technical standards for platform performance, payload optimization, caching strategies, backward compatibility, and graceful offline/fallback behavior across client devices. Cross-Functional Collaboration: Work closely with Product Managers, Design System leaders, and Core Infrastructure engineers to align the Codeless roadmap with broader company initiatives and global design paradigms. What you’ll need to thrive Engineering Management: 3+ years of experience managing software engineering teams, with a track record of coaching engineers, delivering complex platform initiatives, and driving technical strategy. UI & Platform Domain Expertise: Strong foundational background in mobile (iOS/Android) or modern web architecture (React, SwiftUI, Jetpack Compose, or declarative UI paradigms). Product & Platform Mindset: Ability to treat internal product engineering teams as customers, evaluating platform success through developer velocity, adoption metrics, and rendering performance. Why join us At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. 💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. ➡️ Want a deeper look at how we build? Check out our Tech Blog. We aim to create a fair process that lets your skills shine—our interview typically includes 3-4 stages. Explore our Engineering Interview Guide here to help you feel confident at each stage. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: AU: Melbourne: (260 Burwood Rd); AU: Queensland Remote Worker; AU: New South Wales Remote Worker; AU: Sydney (45 Clarence St); AU: Brisbane (243 Edward St); AU: Victoria Remote Worker Workplace: Hybrid SENIOR ENGINEER - PLATFORM The role and its impact As a Senior Engineer in our Infrastructure team, you’ll help Xero engineers build and test software faster and with more confidence. You’ll design and build the systems that create test environments, and you’ll make sure test data is ready when teams need it. This work sits at the heart of how we ship software, and it helps set Xero up for AI transformation. You’ll work across complex platforms, including older legacy systems alongside modern technology. There will be trade-offs to weigh as you decide where the most value sits for engineering teams. Xero asks you to Go Bold in how you approach these problems, and to Go Fast without cutting corners. The team and how they connect Our Infrastructure team builds the platform foundations that Xero engineers rely on every day. Our engineers come from software, platform and infrastructure backgrounds, and we work closely with teams across Xero to understand their systems and find elegant solutions. We believe in Going Together, which means sharing knowledge openly and making sure everyone’s voice is heard. The team is currently working on / Initially, you will focus on: - Building support systems and tooling for test environments, so engineers can test changes without waiting on blockers. - Improving test data and enabling frictionless testing across engineering teams. - Working with our Golang services, alongside infrastructure built with Terraform on AWS, including Kubernetes, EC2 and Lambda. - Contributing to a longer-running initiative to shorten feedback loops and increase engineering productivity. Where and how you can work This is a permanent role, based in Melbourne, Sydney or Brisbane with a remote-first working culture. We have no set office days, so you’ll work with your manager and team to find a balance that suits how you do your best work. Once you’ve settled in, you’ll join our on-call rotation as part of supporting the systems we build. Here are some of the things we’re looking for, for this role: - Your background could be in software engineering that has moved into platform or DevOps, or in infrastructure work that understands how software is built. - Golang is our preferred language, though strong experience in Java or .NET is equally welcome. - Hands-on experience with Terraform, AWS and Kubernetes will help you hit the ground running. - A curious, problem-solving mindset and the ability to pick up unfamiliar systems quickly, including legacy ones, are key to how you’ll Go Further here. - Clear communication is second nature to you, whether you’re working in another team’s codebase or presenting to leadership. Apply even if your experience isn’t a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: NZ: Wellington: Xero One (19-23 Taranaki St); NZ: Auckland: Xero 4 (96 St Georges Bay Rd, Level 2 & 3) Workplace: Hybrid The role and its impact Xero’s customers discover, learn about and get support through our customer-facing web experiences, and you’ll help shape them. As our Lead Engineer, you’ll design and build modern React + next.js and TypeScript experiences that connect Xero’s core ecosystem with our public web presence, from the first visit to getting help. You’ll set the architecture for a multi-site platform that brings together React and Salesforce Experience Cloud surfaces, and lead one of our two engineering pods as the platform grows. This is a chance to build something modern rather than maintain a monolith. You’ll make performance and accessibility the default, explore AI and agentic solutions in customer experiences, and partner with Product, Marketing and Support to bring new ideas to life. You will Go Bold by challenging the status quo, and Go Further by making the experience better for customers around the world. The team and how they connect Our Customer Platforms team build the experiences customers use to learn, get support and find what they need. You’ll work across two closely connected pods, we work in an agile way, with regular planning, retros and demos, and we value open dialogue and psychological safety. The team is currently working on - Tech stack: TypeScript, React and Next.js, with API-driven content layers, a headless CMS, a composable architecture and AWS backend infrastructure. - Reimagining parts of Xero Central to deliver greater value through a modern, frictionless customer expereince. - Running a hybrid React and Salesforce Experience Cloud estate while bringing in new AI-powered features. - Shaping the target architecture for Xero’s customer experiences, including agentic AI proofs of concept. Where and how you can work This role can be based in Wellington or Auckland. Our hybrid approach asks for around one day per week in the office as a minimum, so you can connect with your pod and stakeholders in person. Here are some of the things we’re looking for, for this role: - You bring deep experience with TypeScript, React and Next.js at architecture level, including designing high-performance, content-rich multi-site platforms. - Migrating live, high-traffic sites without disruption is familiar territory, and you can plan a careful, low-risk path to get there. - Performance and accessibility are second nature to you, with a working knowledge of Core Web Vitals and WCAG. - Coaching engineers is part of how you lead, and you’ll Go Together with teams as they build new skills in React and AI. - You’re comfortable leading through influence, and you Go Bold by pushing back constructively when something isn’t right for customers. - Experience across e-commerce, media, agency or other high-traffic web environments gives you fresh views on performance and customer experience. Apply even if your experience isn’t a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role and its impact Xero’s customers discover, learn about and get support through our customer-facing web experiences, and you’ll help shape them. As our Lead Engineer, you’ll design and build modern React + next.js and TypeScript experiences that connect Xero’s core ecosystem with our public web presence, from the first visit to getting help. You’ll set the architecture for a multi-site platform that brings together React and Salesforce Experience Cloud surfaces, and lead one of our two engineering pods as the platform grows. This is a chance to build something modern rather than maintain a monolith. You’ll make performance and accessibility the default, explore AI and agentic solutions in customer experiences, and partner with Product, Marketing and Support to bring new ideas to life. You will Go Bold by challenging the status quo, and Go Further by making the experience better for customers around the world. The team and how they connect Our Customer Platforms team build the experiences customers use to learn, get support and find what they need. You’ll work across two closely connected pods, we work in an agile way, with regular planning, retros and demos, and we value open dialogue and psychological safety. The team is currently working on - Tech stack: TypeScript, React and Next.js, with API-driven content layers, a headless CMS, a composable architecture and AWS backend infrastructure. - Reimagining parts of Xero Central to deliver greater value through a modern, frictionless customer expereince. - Running a hybrid React and Salesforce Experience Cloud estate while bringing in new AI-powered features. - Shaping the target architecture for Xero’s customer experiences, including agentic AI proofs of concept. Where and how you can work This role will be based in Melbourne. Our hybrid approach asks for around one day per week in the office as a minimum, so you can connect with your pod and stakeholders in person. Here are some of the things we’re looking for, for this role: - You bring deep experience with TypeScript, React and Next.js at architecture level, including designing high-performance, content-rich multi-site platforms. - Migrating live, high-traffic sites without disruption is familiar territory, and you can plan a careful, low-risk path to get there. - Performance and accessibility are second nature to you, with a working knowledge of Core Web Vitals and WCAG. - Coaching engineers is part of how you lead, and you’ll Go Together with teams as they build new skills in React and AI. - You’re comfortable leading through influence, and you Go Bold by pushing back constructively when something isn’t right for customers. - Experience across e-commerce, media, agency or other high-traffic web environments gives you fresh views on performance and customer experience. Apply even if your experience isn’t a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

What you’ll do Build new APIs and trading products, from researching the problem and designing the architecture to shipping the first version. Maintain and extend our existing APIs, including support for new chains, bridges and customer-requested features.

Location: United States; Canada; Mexico; Costa Rica; Panama; Guatemala About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.

Location: Brazil; Argentina; Colombia; Chile; Peru; Uruguay About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.

Location: United Kingdom; Germany; Poland; South Africa; United Arab Emirates; Egypt About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.