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Location: New York; San Francisco; London Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We’re looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you’ll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads: LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You’ll help teams reach outcomes most engineers can’t on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We’re looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. WHAT YOU’LL WORK ON: - Work hands-on with companies like Suno, Cognition, and Meta to architect and optimize production AI workloads on Modal - Contribute to open-source projects (members of the team are active contributors to SGLang) and publish technical content that demonstrates Modal’s capabilities across the AI stack - Collaborate with Modal’s product and sales teams, contributing to the platform as both an engineer and a product stakeholder - Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work - Conduct technical demos, experiments, and proofs of concept that make Modal’s performance advantages tangible YOU MAY BE A FIT IF: - You have 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure - You’re familiar with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains and can go deep on at least one (you don’t need all of them) - You’re a strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership - You have a genuine interest in working directly with customers: you find it energizing to understand someone else’s problem and help them solve it - You’re willing to work in person in New York City, San Francisco, or Stockholm NICE-TO-HAVE: - Side projects, open-source contributions, or published work you’re proud of in ML or systems performance

Location: London, UK Workplace: OnSite Recraft is a graphic design research lab building state-of-the-art image generation models and tools for designers, illustrators, marketers, and developers. Founded in 2022 and based in London, we build for commercial design standards: full creative control, style consistency, and native vector outputs, an API for teams who want to integrate that capability directly into their workflows, plus mobile app for those who prefer not to be distracted from the process without a computer. Over 3 million creators across 190+ countries use Recraft. Our mission is to help everyone who works with visuals get the job done, without lowering the bar on design. If you want to help set that standard, we'd like to hear from you. JOB DESCRIPTION We are looking for experienced Research Engineers to develop and optimise AI models, conduct cutting-edge research, and push the boundaries of AI and machine learning. Whether your expertise lies in AI model development, applied research, or production-level deployment, this role offers the opportunity to work at the forefront of generative AI innovation. KEY RESPONSIBILITIES - Develop and train large-scale generative models, pushing the boundaries of AI capabilities. - Design and run experiments to explore and refine model architectures, analyze results, and implement data-driven improvements. - Continuously innovate by developing and deploying new features that enhance user experiences. ‍ REQUIREMENTS - Proven experience in training large-scale generative models (e.g., image generation, audio synthesis, or large language models). - Expertise in evaluating generative models, with a deep understanding of qualitative and quantitative metrics. - Strong proficiency in PyTorch and familiarity with state-of-the-art neural network architectures. - Hands-on experience building end-to-end machine learning pipelines, including data collection and pre-processing, model training and evaluation, inference serving. - Strong software engineering skills, ability to design, implement and maintain high-quality code. - English: B2+ (Upper-Intermediate or above), written and spoken. ‍ WHAT WE OFFER - Competitive salary and equity. - Opportunities for professional growth and leadership. - A collaborative, research-driven environment. - The chance to work on cutting-edge AI projects that redefine creative workflows. - The opportunity to contribute to open-source AI research and publications. - Full-time, on-site role. - We’re able to offer Skilled Worker visa sponsorship in the UK for qualified candidates. ‍

Location: Remote We are seeking an ML Engineer who will assist in constructing a system to validate data and ML models. The ideal candidate should be intelligent, contemplative, and composed. They should not rush through tasks, instead diving deeply into the code and being attentive to details. WHAT YOU’LL BE DOING: The task involves the development and upkeep of data pipelines for training and evaluating models Exploratory data analysis will be conducted to enhance model accuracy and performance Experiments and evaluations of machine learning models will be carried out to identify and address any issues WHAT WE LOOK FOR IN YOU: Strong experience in machine learning Experience in developing and deploying machine learning pipelines and workflows, including data preprocessing, feature engineering, model training, and evaluation Strong analytical and problem-solving skills, as well as attention to details WHY SHOULD YOU JOIN OUR TEAM? Great challenges with many opportunities to prove yourself A welcoming group of highly qualified international professionals Cutting-edge hardware and technology Work remotely from anywhere in the world Access any of our global offices anytime 40 paid days off Competitive salary and performance-based bonuses

Location: Москва В команду сервиса “Новостной мониторинг” требуются Middle ML Engineer. Мы занимаемся разработкой NLP моделей для анализа новостного потока, ключевые задачи: NER, entity linking, классификация. У нас открывается новое направление по OCR. Необходимо будет автоматизировать входящий поток документов в разных форматах. Обязанности ### Задачи: * Есть end-to-end real-time пайплайн обработки новостей - от парсинга до поставки пользователям. Внутри происходит много чего интересного, но не всегда оптимально. Ожидается, что грамотный MLE поможет нам с этим. * Есть задачи по организации хранения данных (сейчас сделано медленное хранилище в PostgreSQL, быстрое - ElasticSearch), по микросервисной архитектуре (есть много докер-контейнеров, можно попробовать все в кубер затащить) и по деплою моделей (хочется организовать автоматическую выкатку в torchserve через gitlab-ci + ansible) Требования ### Требования: * Уверенный Python, SOLID, умение разбираться в чужом коде * БД: PostgreSQL, знание ElasticSearch будет плюсом * ML/DL - sklearn/Pytorch, знание transformers будет плюсом * Gitlab CI, Docker, ansible * Желательно иметь опыт заворачивания торчевых моделей в onnx/tensorrt Условия ### Условия: * ML Space для обучения моделей * Крупнейшее DS&AI community - более 600 DS банка, включая: * Регулярный обмен знаниями, опытом и лучшими практиками * Возможность переиспользования кода и библиотек из централизованного репозитория * Интерактивные лекции и мастер-классы от ведущих ВУЗов и экспертов технологических компаний * Дайджест о самых последних разработках в области DS&AI * Регулярные внутренние митапы

Location: Limassol Wisebits — is an international IT holding with a strong technical team! Our key product is a high-load video hosting platform used by millions of people worldwide every day. With over 15 years on the market, we’ve built a professional team that values engagement and initiative. If you’re excited about working with a high-load product and want to have an impact on its development, join us! What you'll be working on: Participating in the development and improvement of recommendation systems, including user-item, item-item, and cross-platform recommendations. Optimizing recommendations on category, channel, and tag pages. Building text-to-video search: embedding models, ranking, and semantic search. Turning ML prototypes into production services: inference optimization, profiling, feature preparation, and model quality control. Developing high-load ML services in Python, including gRPC/Triton-based services. Our stack: Languages and libraries: Python, PyTorch, CatBoost, NumPy, Pandas, Polars, CuDF, CuPy. Infrastructure and deployment: Kubernetes, Docker, Airflow, Triton Inference Server. Data storage: ClickHouse, MySQL. What we expect from you: 2+ years of experience with recommendation systems, search, or related ML tasks. Strong knowledge of Python and ML frameworks, such as PyTorch, CatBoost, etc. Experience deploying models to production. Understanding of offline and online model evaluation principles. What we offer: Work on an ML product used by millions of users, with real product metrics. A compact team where every engineer has an impact on the product and can develop expertise across several areas. Experienced colleagues to discuss ideas with, think through solutions together, and launch new projects and features. A simple structure — minimum bureaucracy, maximum ownership. Benefits package: medical insurance, tax compensation, professional training, work equipment, and language courses. Relocation to Cyprus: visa support, relocation coverage, tickets, and the first month of accommodation. Flexible schedule, a comfortable atmosphere, and team support. Work format: Remote / On-site Salary: From €4,000 net per month. The final compensation level may be higher and depends on relevant experience, skills, and overall match with the role requirements.

Location: Remote Canada At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the team Machine Learning is central to how Affirm delivers on its mission, powering decisions across underwriting, fraud, servicing, and personalization. We are seeking a  Senior Software Engineer to join our ML Training & Serving engineering team, the team that builds and operates the critical infrastructure that enables models to be trained and served across Affirm. This role sits at the intersection of distributed systems, ML infrastructure, and platform engineering. We value engineers who listen closely, invite feedback, and work effectively across organizational boundaries, while maintaining a high bar for ownership, technical judgment, and execution. Strong candidates care about building reliable shared platforms, improving developer velocity, and creating durable systems that enable teams across the company to move faster with confidence. What You'll Do · You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. · You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. · You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. · You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. · You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For · You have 4+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. · You have a track record of developing highly available distributed systems using technologies like AWS, MySQL and Kubernetes. · You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. · You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. · Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. · You have strong verbal and written communication skills that support effective collaboration with our global engineering team. Experience training and deploying models for production is a nice to have. Base Pay Grade - N Equity Grade - 6 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). CAN base pay range per year: $153,000 - $213,000 Location - Remote Canada This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the team Machine Learning is central to how Affirm delivers on its mission, powering decisions across underwriting, fraud, servicing, and personalization. We are seeking a  Senior Software Engineer to join our ML Training & Serving engineering team, the team that builds and operates the critical infrastructure that enables models to be trained and served across Affirm. This role sits at the intersection of distributed systems, ML infrastructure, and platform engineering. We value engineers who listen closely, invite feedback, and work effectively across organizational boundaries, while maintaining a high bar for ownership, technical judgment, and execution. Strong candidates care about building reliable shared platforms, improving developer velocity, and creating durable systems that enable teams across the company to move faster with confidence. What You'll Do · You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. · You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. · You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. · You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. · You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For · You have 4+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. · You have a track record of developing highly available distributed systems using technologies like AWS, MySQL and Kubernetes. · You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. · You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. · Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. · You have strong verbal and written communication skills that support effective collaboration with our global engineering team. · This position requires either equivalent practical experience or a Bachelor’s degree in a related field. · Experience training and deploying models for production is a nice to have. Base Pay Grade - N Equity Grade - 9 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT) per year: $195,000 - $225,000 USA base pay range (all other U.S. states) per year: $173,000 - $233,000 #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote Canada At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Engineering team The Engineering team builds systems that power Affirm’s mission. We take pride in our craft, building reliable, performant, and scalable solutions that touch every part of the business. Whether we’re enabling new ways to pay, ensuring our platforms can scale to the most demanding levels in the industry, or developing seamless servicing experiences, our focus is on solving complex problems through exceptional engineering. About the team ML Feature Platform is one of the two teams that compose the ML Platform at Affirm, the other team being ML Training & Serving Platform. The two platform teams work closely together to create the ML + Data flywheel that empowers Affirm. ML Feature Platform’s mission is to: Grow Affirm’s business by building a delightful, self-serve platform for developing and serving data for machine learning and decisioning. As the feature platform team, we own multiple artifacts that in aggregate own the end-to-end flows for features. This includes: Feature creation, exploration, and serving Data storage, availability, and visibility Offline backfilling infrastructure and platform improvements This scope means your work will have a direct impact on the everyday lives and capabilities for our end users: MLEs, Analysts, and decisioning teams. Additionally as the primary data source for ML and online decisioning, our platform’s performance is critical to Affirm’s availability and latency goals. We’re looking for engineers who are passionate about ML enablement and believe that platform level improvements can bring snowball effects across the company. What you’ll do You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What we look for You have 4+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have a track record of developing highly available distributed systems using technologies like AWS, MySQL and Kubernetes. You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. Base Pay Grade - N Equity Grade - 6 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). CAN base pay range per year: $153,000 - $213,000 Location - Remote Canada This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Engineering team The Engineering team builds systems that power Affirm’s mission. We take pride in our craft, building reliable, performant, and scalable solutions that touch every part of the business. Whether we’re enabling new ways to pay, ensuring our platforms can scale to the most demanding levels in the industry, or developing seamless servicing experiences, our focus is on solving complex problems through exceptional engineering. About the team ML Feature Platform is one of the two teams that compose the ML Platform at Affirm, the other team being ML Training & Serving Platform. The two platform teams work closely together to create the ML + Data flywheel that empowers Affirm. ML Feature Platform’s mission is to: Grow Affirm’s business by building a delightful, self-serve platform for developing and serving data for machine learning and decisioning. As the feature platform team, we own multiple artifacts that in aggregate own the end-to-end flows for features. This includes: Feature creation, exploration, and serving Data storage, availability, and visibility Offline backfilling infrastructure and platform improvements This scope means your work will have a direct impact on the everyday lives and capabilities for our end users: MLEs, Analysts, and decisioning teams. Additionally as the primary data source for ML and online decisioning, our platform’s performance is critical to Affirm’s availability and latency goals. We’re looking for engineers who are passionate about ML enablement and believe that platform level improvements can bring snowball effects across the company. What you’ll do You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What we look for You have 4+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have a track record of developing highly available distributed systems using technologies like AWS, MySQL and Kubernetes. You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. · Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. Base Pay Grade - N Equity Grade - 9 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT) per year: $195,000 - $225,000 USA base pay range (all other U.S. states) per year: $173,000 - $233,000 #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Responsibilities: — Work on Document AI tasks including parsing complex documents and scans — Develop Computer Vision solutions for recognizing floor plans and technical drawings Requirements: — Hands-on experience with Document AI — Hands-on experience with Computer Vision Benefits: — Remote work with 6-hour overlap required with Canada — Full-time position on a long-term project — Immediate start Tech stack includes Python, PyMuPDF, OCR technologies (AWS Textract / Tesseract), Structured LLM Output, OpenCV, Shapely (geometry/polygons), and SVG generation.

Responsibilities: — Design, deploy, and operate production AI infrastructure for customer workloads. Requirements: — Experience with machine learning, Kubernetes, Java, Spark, IAM, Infrastructure-as-Code, Go, Terraform, networking, distributed computing, GCP, Python, GitOps, Dask, DevOps, AWS, Helm, CI/CD, and Security. Benefits: — Salary range $250,000 - $275,000.

Location: Ukraine; Poland; Romania; Spain; Portugal; Croatia At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. We are looking for a Senior ML & AI Engineer to join us as part of our team. About the role PitchBook’s Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high-volume of data for the PitchBook Platform and surface insights for the capital markets. This role will also serve as a resource and mentor for junior members of the team. A strong motivation to succeed is critical and everyone has the opportunity to shape the long-term direction of our team. About the project PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials and many more. Team 1 EM, 6 ML Engineers Work Environment The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology. As a qualified expert, You will Work with GenAI & LLMs: Design, develop, and fine-tune generative AI models using transformer architectures. Implement advanced techniques to create practical solutions for real-world challenges. Use Modern Toolkits: Leverage frameworks like LangChain, LangGraph, and LangSmith to build automated pipelines and intelligent agents. Integrate these tools with vector databases for efficient similarity search and real-time analysis. Extract Data Insights: Process and analyze large volumes of unstructured data using embeddings and statistical modeling to identify meaningful insights. Build Scalable Systems: Collaborate with cross-functional teams to create production-grade ML systems that handle real-time, high-volume data processing. Mentor & Lead: Act as a mentor for junior team members and stay updated on trends in Agentic AI, transformer models, and generative systems. Collaborate & Communicate : Work with Product and Engineering teams to improve data management and support innovation. Present complex analyses clearly and effectively. Tech Stack & Focus Areas: Work with generative AI and transformer models, integrating frameworks like LangChain, LangGraph, and LangSmith to automate workflows and build intelligent systems. Use PyTorch, Scikit-Learn, and Spacy to build NLP pipelines. Implement vector databases for high-dimensional data embeddings and develop hybrid models to extract insights from diverse data sources. We’re looking for you if you have Educational Background: You hold a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field. Experience: You bring 5+ years of production experience in the ML field, with a track record in developing transformer-based models and deploying them in scalable systems. Technical Expertise: Proficient in Python and machine and deep learning frameworks like TensorFlow, PyTorch, ScikitLearn, Spacy or other. Experienced in natural language processing and modern LLM based techniques. Experience with full ML lifecycle, data preprocessing, training, evaluation stages and monitoring techniques Skilled with SQL and data extraction methods. Innovative Thinker: You thrive on solving complex problems and are always exploring new trends in Generative AI. Collaborator & Communicator: You’re an excellent communicator able to collaborate and express your thoughts in a professional manner to team members, other engineering teams and stakeholders. Domain Knowledge: Exposure to financial services, investment banking, venture capital, or private equity is nice to have. Languages: English —Upper-Intermediate or higher; Ukrainian —fluent/native . What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work. Embrace the opportunity for personal and professional growth Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more. Be among like-minded people Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program. Interview steps Interview with the recruiter Technical interview (up to 90 min) System Design interview (up to 45 min) Behavioral Round with Product Manager (45 min) Final interview with Engineering Manager (30 min)

Location: London; Europe; Berlin; United Kingdom Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS TEAM? Internal Infrastructure builds the infrastructure and tools used to train, evaluate, and serve Cohere's foundation models. You will work with AI researchers and ML engineers on stability, scalability, and observability. The work accelerates the models behind Cohere's platform, North. You will own the developer platform researchers use to write, build, and debug training code: dev environments, container images, CI, and training instrumentation. The role includes a compensated 24x7 on-call rotation. WHAT YOU WILL DO - Run secure developer environments that stay controlled and accelerate developer velocity as the research org scales. - Own container image build and CI/CD tooling. - Instrument training code and build self-service tooling so researchers can see why a run failed and debug it themselves. - Set infrastructure best practices through AI enablement, documentation, and office hours. - Troubleshoot production failures and performance problems, and leave the system easier to operate than you found it. - Build automation, infrastructure-as-code, and observability so the platform stays maintainable. We hire at more than one level. We set level based on the scope you've owned and how independently you drive work. YOU MAY BE A GOOD FIT IF YOU HAVE - Run a developer platform in production: CI, image builds, dev environments, or internal tooling that many engineers depend on. - Made ML engineers or researchers faster without making the platform fragile. - Enough Linux and Kubernetes to debug production systems. Experience operating a GPU cluster is a plus. - Written software in Python or Go. You would rather extend a solid open-source project than rebuild it. - Worked with researchers, ML engineers, or another team whose goals were not identical to yours. - Found a bottleneck, proposed a fix, and driven it in a fast-moving environment. If this does not line up exactly with your experience, we still encourage you to apply. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Canada; United States Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS TEAM? Internal Infrastructure builds the infrastructure and tools used to train, evaluate, and serve Cohere's foundation models. You will work with AI researchers and ML engineers on stability, scalability, and observability. The work accelerates the models behind Cohere's platform, North. You will build the platform that runs training, evaluation, and reinforcement-learning workloads: job lifecycle, scheduling, workload networking, and the storage those jobs depend on. The role includes a compensated 24x7 on-call rotation. WHAT YOU WILL DO - Own the platform that schedules and runs training, evaluation, and reinforcement-learning jobs on Kubernetes: who gets capacity, what happens when a job fails, and how a researcher finds out whether the platform caused it. - Build the networking and runtime isolation those workloads need, including agent and sandbox environments. - Work with the data infrastructure team on storage for checkpoints and other training artifacts. - Troubleshoot production failures and performance problems, and leave the system easier to operate than you found it. - Build automation, infrastructure-as-code, and observability so the platform stays maintainable. We hire at more than one level. We set level based on the scope you've owned and how independently you drive work. YOU MAY BE A GOOD FIT IF YOU HAVE - Run a job platform, batch system, or Kubernetes controllers in production. Scheduling, queues, and multi-tenant fairness are central to this work. - Shown distributed systems judgment: retries, partial failure, and knowing what not to automate. - Worked on ML training workflows, RL sandboxes, container networking (CNI), or checkpoint storage at scale. Direct GPU-cluster experience is a plus. - Written software in Python or Go. You would rather extend a solid open-source project than rebuild it. - Worked with researchers, ML engineers, or another team whose goals were not identical to yours. - Found a bottleneck, proposed a fix, and driven it in a fast-moving environment. If this does not line up exactly with your experience, we still encourage you to apply. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Задачи: — Функциональное и системное сопровождение банковского программного обеспечения — Сопровождение и развитие инфраструктуры банковского программного обеспечения — Обеспечение доступности автоматизированных банковских процессов — Осуществление технической поддержки пользователей и клиентов — Накопление и передача технической экспертизы по архитектуре ИТ системы, а также по бизнес-процессам — Развитие программно-инфраструктурного ландшафта банка — Реализация пилотных проектов бизнеса Требования: — Управление серверами на базе Linux на уровне администратора — Знание СУБД на уровне администратора: PostgreSQL(Patroni), Redis, MongoDB — Знание микросервисной архитектуры и технологий контейнеризации: Docker, containerd — Продвинутые навыки работы с Kubernetes, Helm, Kafka — Понимание принципов построения процессов CI/CD — Понимание принципов IaC — Продвинутые навыки работы с Ansible, Terraform, Terragrunt — Понимание принципов построения Observability — Продвинутые навыки работы с ELK/EFK, OpenSearch, Prometheus, VictoriaMetrics — Опыт работы с облачными провайдерами, например, AWS, Yandex Cloud — Навыки программирования, например, на Python, GO, Java, JavaScript Условия: — Полная занятость — График работы 5/2 — Формат работы: удалённо

Location: Canada, Waterloo, ON 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. At PlayStation, we're passionate about both partnership and technology. We care about building performant products and powerful tools, solving practical problems in delightful ways. We love building the systems that millions of people use, and we're always our own first customers and critics. We strive to be at the forefront of development technologies and celebrate our diversity with engineering teams located on four continents from all walks of life. We build our teams to be places where every voice is heard, all input is valued, and our members have the creative freedom to make their ideas real. Sr Software Development Engineer in Test , ML Locations: Madison, WI and Waterloo, Ontario Canada P layStation is seeking a Sr Software Development Engineer in Test, ML to join our Madison team and lead quality efforts for machine learning-powered products and services. You will partner closely with ML engineers, software engineers, product managers, and data partners to build scalable test automation and validation approaches for systems serving PlayStation at global scale. This role is focused on building confidence in model reliability, production readiness, and behavioral consistency. Unlike traditional software backend testing, success here requires validating probabilistic systems through score distributions, cohort-level behavior, thresholds, and statistical signals, not just deterministic pass/fail assertions. Responsibilities: Drive architecture-level automation solutions and scalable quality engineering practices across multiple teams and product areas. Design, develop, and maintain automated test frameworks, test scripts for ML inference services and related ML platform components using python/Java Build and automate realistic, representative test account creations and datasets to evaluate model behavior across different scenarios Validate score distributions, ranking behavior, output quality, and other model signals for incoming ML models prior to release Perform different types of testing, including functional, integration, regression and API testing working with RESTful APIs, microservices and databases, and non-functional performance and load testing to verify inference service scalability, latency requirements and reliability under production like conditions Work closely with ML engineers and ops teams to ensure that all features and bug fixes come with automated test coverage, ensuring continuous integration and deployment Debug and analyze test failures, model anomalies and report defects Drive high standards of quality for both engineering decisions and customer-facing features with optimal test and automation strategy Develop and implement best practices for test automation that is highly scalable and maintainable Monitor test execution and optimize performance in test environments Come up with innovative solutions to organizational problems Required Qualifications: A Bachelor's degree in Computer Science or related field Minimum 5 years of experience as an SDET, with strong experience testing backend systems. Proficiency in Python/Java/Scala/go for test automation. Hands-on experience with API testing tools (e.g., Postman or similar) for distributed systems Familiarity with CI/CD pipelines and test execution in Jenkins or similar environments such as jenkins, GitHub Actions, ArgoCD, etc Hands-on experience building and maintaining automated test frameworks (e.g., pytest, JUnit, TestNG, etc.)Experience in working with databases  for backend validation. Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker, etc.) Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, etc.) for validating service health Strong understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and excellent communication skills. Preferred Qualifications: Experience testing machine learning systems, such as recommendation systems, search ranking systems, or other probabilistic ML application systems. Experience creating synthetic or seeded test data to simulate realistic customer/account behaviors. Experience evaluating model outputs using statistical techniques, distribution analysis, or scenario-based validation, rather than deterministic assertions. Knowledge of data pipelines, feature stores, inference systems or model-serving infrastructure (Seldon, KServe, Ray Serve, etc.) is a plus. Experience with performance and load testing tools Experience with Databricks or similar ML platform tooling Experience architecting and optimizing CI/CD pipelines, quality gates, and release validation systems using Jenkins or similar platforms. 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. The estimated Ontario base pay range for this role is listed below. $114,000 — $143,000 CAD 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: United States, Madison, WI 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. At PlayStation, we're passionate about both partnership and technology. We care about building performant products and powerful tools, solving practical problems in delightful ways. We love building the systems that millions of people use, and we're always our own first customers and critics. We strive to be at the forefront of development technologies and celebrate our diversity with engineering teams located on four continents from all walks of life. We build our teams to be places where every voice is heard, all input is valued, and our members have the creative freedom to make their ideas real. Sr Software Development Engineer in Test , ML Locations: Madison, WI and Waterloo, Ontario Canada P layStation is seeking a Sr Software Development Engineer in Test, ML to join our Madison team and lead quality efforts for machine learning-powered products and services. You will partner closely with ML engineers, software engineers, product managers, and data partners to build scalable test automation and validation approaches for systems serving PlayStation at global scale. This role is focused on building confidence in model reliability, production readiness, and behavioral consistency. Unlike traditional software backend testing, success here requires validating probabilistic systems through score distributions, cohort-level behavior, thresholds, and statistical signals, not just deterministic pass/fail assertions. Responsibilities: Drive architecture-level automation solutions and scalable quality engineering practices across multiple teams and product areas. Design, develop, and maintain automated test frameworks, test scripts for ML inference services and related ML platform components using python/Java Build and automate realistic, representative test account creations and datasets to evaluate model behavior across different scenarios Validate score distributions, ranking behavior, output quality, and other model signals for incoming ML models prior to release Perform different types of testing, including functional, integration, regression and API testing working with RESTful APIs, microservices and databases, and non-functional performance and load testing to verify inference service scalability, latency requirements and reliability under production like conditions Work closely with ML engineers and ops teams to ensure that all features and bug fixes come with automated test coverage, ensuring continuous integration and deployment Debug and analyze test failures, model anomalies and report defects Drive high standards of quality for both engineering decisions and customer-facing features with optimal test and automation strategy Develop and implement best practices for test automation that is highly scalable and maintainable Monitor test execution and optimize performance in test environments Come up with innovative solutions to organizational problems Required Qualifications: A Bachelor's degree in Computer Science or related field Minimum 5 years of experience as an SDET, with strong experience testing backend systems. Proficiency in Python/Java/Scala/go for test automation. Hands-on experience with API testing tools (e.g., Postman or similar) for distributed systems Familiarity with CI/CD pipelines and test execution in Jenkins or similar environments such as jenkins, GitHub Actions, ArgoCD, etc Hands-on experience building and maintaining automated test frameworks (e.g., pytest, JUnit, TestNG, etc.)Experience in working with databases  for backend validation. Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker, etc.) Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, etc.) for validating service health Strong understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and excellent communication skills. Preferred Qualifications: Experience testing machine learning systems, such as recommendation systems, search ranking systems, or other probabilistic ML application systems. Experience creating synthetic or seeded test data to simulate realistic customer/account behaviors. Experience evaluating model outputs using statistical techniques, distribution analysis, or scenario-based validation, rather than deterministic assertions. Knowledge of data pipelines, feature stores, inference systems or model-serving infrastructure (Seldon, KServe, Ray Serve, etc.) is a plus. Experience with performance and load testing tools Experience with Databricks or similar ML platform tooling Experience architecting and optimizing CI/CD pipelines, quality gates, and release validation systems using Jenkins or similar platforms. 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. $152,000 — $190,000 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: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team. Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.   The team You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business. Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.   Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for - A track record of designing, shipping and operating production-grade backend systems at scale - Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences - A coaching mindset and the ability to set engineering standards and mentor other engineers Nice to have - Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)   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.