Вакансии

Location: Germany Workplace: Remote The Connectors team is the bridge between ClickHouse and the broader ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide, from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling. Our work directly shapes how companies process massive datasets: real-time analytics platforms that ingest millions of events per second, observability systems that monitor global infrastructure, and, increasingly, AI-powered data applications that redefine how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience. ABOUT THE ROLE As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use. We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why. You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications. ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems. WHAT YOU'LL DO - Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design - Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications - Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback - Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities - Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows ABOUT YOU - 7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer - Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation) - Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production - Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries - Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases - Solid experience with concurrent Python: threading, multiprocessing, and async patterns - Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities Bonus points for: - Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role - Familiarity with ClickHouse or similar high-performance OLAP platforms - Familiarity with the JVM ecosystem - Experience deploying AI/ML models in production, including inference APIs and vector databases - Familiarity with tools like dbt, Airflow, Dagster, Prefect is a plus PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Spain Workplace: Remote The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling. Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience. WHAT YOU'LL DO - Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design - Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards - Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications - Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback - Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities - Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows ABOUT YOU - 7+ years of software development experience, including hands-on time as a Data Engineer, Data Scientist, or ML Engineer - Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation) - Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production - Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries - Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases - Solid experience with concurrent Python: threading, multiprocessing, and async patterns - Outstanding written and verbal communication; comfortable collaborating across e The Connectors team is the bridge between ClickHouse and the broader ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide, from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling. Our work directly shapes how companies process massive datasets: real-time analytics platforms that ingest millions of events per second, observability systems that monitor global infrastructure, and, increasingly, AI-powered data applications that redefine how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience. ABOUT THE ROLE As a Senior Software Engineer specialising in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use. We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why. You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications. ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems. WHAT YOU'LL DO - Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design - Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications - Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback - Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities - Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows ABOUT YOU - 7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer - Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation) - Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production - Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries - Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases - Solid experience with concurrent Python: threading, multiprocessing, and async patterns - Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities Bonus points for: - Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role - Familiarity with ClickHouse or similar high-performance OLAP platforms - Familiarity with the JVM ecosystem - Experience deploying AI/ML models in production, including inference APIs and vector databases - Familiarity with tools like dbt, Airflow, Dagster, Prefect is a plus PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Israel Workplace: Remote The Connectors team is the bridge between ClickHouse and the broader ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide, from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling. Our work directly shapes how companies process massive datasets: real-time analytics platforms that ingest millions of events per second, observability systems that monitor global infrastructure, and, increasingly, AI-powered data applications that redefine how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience. ABOUT THE ROLE As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use. We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why. You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications. ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems. WHAT YOU'LL DO - Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design - Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications - Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback - Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities - Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows ABOUT YOU - 7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer - Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation) - Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production - Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries - Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases - Solid experience with concurrent Python: threading, multiprocessing, and async patterns - Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities Bonus points for: - Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role - Familiarity with ClickHouse or similar high-performance OLAP platforms - Familiarity with the JVM ecosystem - Experience deploying AI/ML models in production, including inference APIs and vector databases - Familiarity with tools like dbt, Airflow, Dagster, Prefect is a plus PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: United States Workplace: Remote The Connectors team is the bridge between ClickHouse and the broader ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide, from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling. Our work directly shapes how companies process massive datasets: real-time analytics platforms that ingest millions of events per second, observability systems that monitor global infrastructure, and, increasingly, AI-powered data applications that redefine how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience. ABOUT THE ROLE As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use. We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why. You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications. ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems. WHAT YOU'LL DO - Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design - Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications - Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback - Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities - Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows ABOUT YOU - 7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer - Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation) - Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production - Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries - Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases - Solid experience with concurrent Python: threading, multiprocessing, and async patterns - Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities Bonus points for: - Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role - Familiarity with ClickHouse or similar high-performance OLAP platforms - Familiarity with the JVM ecosystem - Experience deploying AI/ML models in production, including inference APIs and vector databases - Familiarity with tools like dbt, Airflow, Dagster, Prefect is a plus PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Meet Arago and the Aragonians Arago is an AI and computer hardware company whose mission is to drive the course of history forward. We do so by accelerating breakthroughs at the intersection of AI and semiconductors. Founded in 2024 by AI researchers and physicists with deep expertise in photonics, electronics, software, mathematics, and machine learning, Arago brings together a lean team of engineers and scientists from the world’s top companies and research labs. Composed of nine nationalities and operating from hubs in France, North America, and Israel, we believe in great science and fast achievements. Our work is guided by these core principles: Do great things: we deliver work we’re proud to sign our name to. High velocity: speed matters. We move quickly, one step at a time. One unit: we’re all in this together, with relationships grounded in trust, respect, and camaraderie. Arago is backed by executives from Apple, Arm, Nvidia, Microsoft, and Hugging Face, as well as prominent US and European deeptech venture firms and exited founders. Задачи: — Develop Arago’s quantization strategy for modern AI models, including precision studies, numerical format exploration, and model-level techniques to preserve accuracy under constrained precision. — Study the impact of analog noise on the performance and inference accuracy of machine learning models, including language models, diffusion, video generation, and world models. — Develop simulation tools to model analog behavior with minimal computational overhead. — Build and maintain Arago's internal experimentation pipelines for precision and performance studies on both physical and emulated prototypes. — Act as a technical point of contact between clients and Arago: analyze, port, and optimize client models onto Arago hardware, balancing throughput and accuracy. — Collaborate with the software and digital architecture teams to support architectural enhancements based on the operator content of frontier model architectures. Требования: — Background in mathematics, physics, computer science, or a related quantitative field. — Strong interest and skills in applied mathematics and statistics. — Strong experience with quantization of machine learning and AI models. — Strong understanding of modern model architectures, including language models, diffusion models, video generation models, and/or world models. — Experience studying the impact of numerical precision, noise, or approximation on model accuracy. — Experience with inference performance optimization. — Good knowledge of computer architecture, GPU architecture, or parallel computing. — Ability to build rigorous experimentation pipelines and translate research insights into practical engineering decisions. — GitHub profile with recent and relevant projects. — Language: English at a proficient level. French is a plus. Условия: — Competitive cash compensation, with final package based on location, experience, and the pay of team members in similar positions. — Meaningful stock option plan offered at the earliest stage of the company (included in the majority of full time offers). — Relocation bonus and coverage of moving expenses for relocation within 20 minutes of the company’s location. — Healthcare coverage (including family-friendly options), pension contributions, professional development support, and 25 days of PTO, in addition to public holidays. — Ownership of a key technical domain, with significant vertical and/or horizontal growth opportunities, based on performance and individual drive. — Reimbursement of 50% of the public transport subscription fee. — A high-paced, multicultural (with 10 nationalities), and engineering-led environment.

Meet Arago and the Aragonians Arago is an AI and computer hardware company whose mission is to drive the course of history forward. We do so by accelerating breakthroughs at the intersection of AI and semiconductors. Founded in 2024 by AI researchers and physicists with deep expertise in photonics, electronics, software, mathematics, and machine learning, Arago brings together a lean team of engineers and scientists from the world’s top companies and research labs. Composed of nine nationalities and operating from hubs in France, North America, and Israel, we believe in great science and fast achievements. Our work is guided by these core principles: Do great things: we deliver work we’re proud to sign our name to. High velocity: speed matters. We move quickly, one step at a time. One unit: we’re all in this together, with relationships grounded in trust, respect, and camaraderie. Arago is backed by executives from Apple, Arm, Nvidia, Microsoft, and Hugging Face, as well as prominent US and European deeptech venture firms and exited founders. What you’ll do As a Senior AI/ML Scientist, you will work at the intersection of modern AI models, numerical precision, and novel computing architectures. Your mission will be to develop the methods that allow AI models to run accurately, efficiently, and reliably on Arago’s computing system. This position combines strong quantization and “digital twin” aspects: understanding how frontier models tolerate reduced precision, defining the right numerical formats and quantization strategies, and building software representations of the processor to model the physical effects that impact AI model accuracy. This role is both scientific and practical. You will help shape the bridge between AI models and Arago’s hardware. Required Skills and Experience Background in mathematics, physics, computer science, or a related quantitative field. Strong interest and skills in applied mathematics and statistics. Strong experience with quantization of machine learning and AI models. Strong understanding of modern model architectures, including language models, diffusion models, video generation models, and/or world models. Experience studying the impact of numerical precision, noise, or approximation on model accuracy. Experience with inference performance optimization. Good knowledge of computer architecture, GPU architecture, or parallel computing. Ability to build rigorous experimentation pipelines and translate research insights into practical engineering decisions. GitHub profile with recent and relevant projects. Language: English at a proficient level. French is a plus. Responsibilities Develop Arago’s quantization strategy for modern AI models, including precision studies, numerical format exploration, and model-level techniques to preserve accuracy under constrained precision. Study the impact of analog noise on the performance and inference accuracy of machine learning models, including language models, diffusion, video generation, and world models. Develop simulation tools to model analog behavior with minimal computational overhead. Build and maintain Arago's internal experimentation pipelines for precision and performance studies on both physical and emulated prototypes. Act as a technical point of contact between clients and Arago: analyze, port, and optimize client models onto Arago hardware, balancing throughput and accuracy. Collaborate with the software and digital architecture teams to support architectural enhancements based on the operator content of frontier model architectures. Pay and benefits Competitive cash compensation, with final package based on location, experience, and the pay of team members in similar positions. Meaningful stock option plan offered at the earliest stage of the company (included in the majority of full time offers). Relocation bonus and coverage of moving expenses for relocation within 20 minutes of the company’s location. Healthcare coverage (including family-friendly options), pension contributions, professional development support, and 25 days of PTO, in addition to public holidays. Ownership of a key technical domain, with significant vertical and/or horizontal growth opportunities, based on performance and individual drive. Reimbursement of 50% of the public transport subscription fee. A high-paced, multicultural (with 10 nationalities), and engineering-led environment.

Задачи: — Развертывать и оптимизировать локальные AI-модели. — Разрабатывать AI-агентов и RAG-решения. — Интегрировать AI-сервисы с корпоративными системами. — Выводить AI-продукты в промышленную эксплуатацию. Требования: — Практический опыт локального развертывания LLM. — Опыт работы с RAG, LoRA/QLoRA, Hugging Face, PyTorch. — Умение доводить AI-продукты до промышленной эксплуатации. — Для Strong Middle обязателен подтвержденный опыт самостоятельной разработки и внедрения AI-решений в production. — Действующее право на трудовую деятельность в Республике Казахстан (оформление разрешений на привлечение иностранной рабочей силы не осуществляется). Условия: — Работа в офисе в Астане, full-time. — Трудовой договор. — Возможность участвовать в создании собственной AI-платформы компании. — Зарплата до 2 000 000 тенге net по результатам интервью.

Задачи: — Ведение полного цикла разработки команды аналитиков и дата-инженеров — Сбор, анализ и формализация требований внутренних заказчиков — Управление сроками, рисками и устранение блокеров — Оптимизация процессов и мониторинг мотивации в команде — Помощь руководителям в управлении перформансом и постановке целей Требования: — Навыки управления кросс-функциональными командами в разработке от 5+ лет — Реальный опыт ведения AI/ML-проектов (LLM/RAG/агенты или классический ML/DS) — Техническая грамотность для диалога с разработчиками и дата-инженерами — Опыт организации полного цикла разработки: бэклог, сроки и риски — Навыки фасилитации командных встреч (Scrum, Kanban, ретроспективы) — Способность самостоятельно принимать решения и соблюдать сроки — Умение декомпозировать задачи в условиях неопределённости Плюсом: — Инженерный бэкграунд (разработка, дата-инженерия, system design) — Знание SQL — Опыт с LLM — Опыт в iGaming Условия: — Стабильная зарплата в EUR по ТК Кипра — Годовой бонус (13‑ая зарплата) — Корпоративное питание в офисе — Тимбилдинги и корпоративные мероприятия — Компенсация спорта и языковых курсов — Возможность релокации через 3 месяца — Оплата обучения и повышения квалификации — Прямое участие в стратегическом развитии компании — Чёткие процессы и профессиональный рост

Задачи: — Ведение полного цикла разработки команды аналитиков и дата-инженеров — Сбор, анализ и формализация требований внутренних заказчиков — Управление сроками, рисками и устранение блокеров — Оптимизация процессов и мониторинг мотивации в команде — Помощь руководителям в управлении перформансом и постановке целей Требования: — Навыки управления кросс-функциональными командами в разработке от 5+ лет — Реальный опыт ведения AI/ML-проектов (LLM/RAG/агенты или классический ML/DS) — Техническая грамотность для диалога с разработчиками и дата-инженерами — Опыт организации полного цикла разработки: бэклог, сроки и риски — Навыки фасилитации командных встреч (Scrum, Kanban, ретроспективы) — Способность самостоятельно принимать решения и соблюдать сроки — Умение декомпозировать задачи в условиях неопределённости Плюсом: — Инженерный бэкграунд (разработка, дата-инженерия, system design) — Знание SQL — Опыт с LLM — Опыт в iGaming Условия: — Стабильная зарплата в EUR по ТК Кипра — Годовой бонус (13‑ая зарплата) — Корпоративное питание в офисе — Тимбилдинги и корпоративные мероприятия — Компенсация спорта и языковых курсов — Возможность релокации через 3 месяца — Оплата обучения и повышения квалификации — Прямое участие в стратегическом развитии компании — Чёткие процессы и профессиональный рост

Location: Tallinn, Estonia Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (Applied AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: A Unique Opportunity for a career in a global, fast-growing company. Attractive remuneration package based on qualifications and experience. Opportunities to learn and grow through our “ Employee Training & Development program”. Stebby Sports Compensation or Confido Health Compensation. Multiple events to bond with the team and the group. Birthday and Loyalty benefits . What to expect from our recruitment process: Interview with HR Assessment task Interview with hiring managers Final interview with top management Make your next Career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Limassol, Cyprus Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: A Unique Opportunity for a career in a global, fast-growing company. Attractive remuneration package based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance). Opportunities to learn and grow through our “ Employee Training & Development program”. Medical Insurance Cover , which includes Outpatient, Inpatient, and Dental Care. Multiple events to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company. Participation in our welfare investment and savings plan through our Provident Fund Scheme. Birthday and Loyalty benefits . Collaboration with SportBenefit. What to expect from our recruitment process: First interview with hiring managers or an HR call Task Assessment Technical Interview or home assignment Final interview with top management Make your next Career step and apply NOW! * Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Chicago, IL, USA; New York, NY, USA; San Francisco, CA, USA About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring AI/ML Engineers across several teams, Trust & Safety, Lending, Growth, and Foundation Models, and you'll be matched with the team where your background, experience and interests fit best. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into decisions that protect members from fraud, expand access to credit, and power the personalized experiences and marketing that help millions of members get more out of products like MyPay, Instant Loans, and SpotMe — along with the foundational models the rest of our teams build on. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters. In this role, you can expect to Build, train, and deploy deep learning and classical ML models on large-scale financial, transactional, and behavioral datasets Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Contribute to the shared ML platform, tooling, and standards that the rest of the team builds on Help identify where AI/ML creates measurable impact for members — and where a simpler answer is the better one To thrive in this role, you have Experience building and deploying deep learning models in production, with a solid grasp of architecture choice, training dynamics, and evaluation — and the judgment to model design choices Solid machine learning fundamentals: classical modeling, evaluation design, and knowing which metric actually answers the question in front of you Hands-on experience across the end-to-end ML lifecycle — training, experimentation, optimization, deployment, and monitoring Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy The ability to operate independently in ambiguous environments, and to communicate clearly with both technical and non-technical partners Nice-to-Have Experience in any one of these is a plus, and helps us match you to the right team. Trust & Safety — fraud, risk, abuse detection, or adversarial modeling Lending — credit or underwriting models, and familiarity with model governance, explainability, and fairness requirements Growth — personalization, recommendation, marketing measurement, or experimentation at scale Foundation Models — transformers on tabular or semi-structured data, large-scale pretraining, ML platform work, or applied research with a publication record #LI-DA1 #LI-Onsite Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $125,000 — $292,000 USD A little about us At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members. We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential. Because if we don't—who will? *Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC. What we offer for our full-time, regular employees 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees. ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life. 🏝 Generous vacation policy and company-wide paid days off 🫂 1% of your time off to support local community organizations of your choice 👟 Annual wellness stipend to use towards eligible wellness related expenses 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents 👪 Access to family planning reimbursement 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com . To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice .

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. Sr. Software Development Engineer In Test, ML/AI At SIE, we believe in making play safer for everyone. Within our Information Security team, we protect our people, platforms, and products with smart, scalable, and thoughtful solutions. Our mission is to provide clear, actionable risk and security insights that guide the business and enable amazing player experiences. We’re building a team that thrives on collaboration, curiosity, and delivering real value. Come help us make a difference! Overview We are hiring a Sr Software Engineer in Test specializing in ML/AI quality, including automation for model evaluation, LLM-assisted test generation, and validation of AI-powered workflows. The role includes guiding quality strategy and developing automation frameworks. You will also manage implementation for complex, cross-functional, machine learning-powered products and services. This role involves more than test development. You will lead quality initiatives from start to finish, ensuring teams stay synchronized, dependencies are managed, and releases are delivered confidently. You will work closely with ML, engineering, product, and infrastructure teams. You will shape how quality is built, monitored, and expanded while leading embedded QE efforts within projects. What you’ll do Define and complete quality strategies, test plans, and automation coverage for ML-powered services and platform components. Use LLMs and other AI-assisted techniques to generate, expand, and maintain high-value test cases for ML-powered workflows. Design scenario-based test suites for AI features, including adversarial prompts, edge cases, ambiguous inputs, and underrepresented user scenarios. Lead QE efforts for multi-functional projects, driving risk assessment, dependency management, and release readiness. Design, develop, and maintain scalable automation frameworks for backend services, APIs, and ML inference systems using Python and/or Java. Build automated validation for ML and LLM outputs, including ranking behavior, score distributions, prompt/response quality, hallucination indicators, and probabilistic model evaluation. Debug test failures, service anomalies, model inconsistencies, and AI behavior regressions to identify root causes and drive resolution. Perform functional, integration, regression, API, end-to-end, performance, and reliability testing for distributed systems. Improve automation reliability, reduce flakiness, and optimize execution efficiency. Partner with engineering and ML teams to integrate automated testing into CI/CD pipelines and release workflows. Collaborate across teams to establish scalable quality standards, tooling, and guidelines. Required qualifications Bachelor’s degree in Computer Science or equivalent 5+ years of experience as an SDET or QE engineer focused on backend and distributed systems. Experience using LLMs to generate, transform, and prioritize test cases for AI-powered experiences. Experience with AI evaluation tooling, prompt evaluation frameworks, model monitoring, or human-in-the-loop review workflows. Strong experience testing RESTful APIs, microservices, and distributed architectures. Proficiency in Python, Java, JS or similar languages for automation development. Hands-on experience with automation frameworks such as pytest, JUnit, Selenium, Playwright, Cypress, or Appium. Experience with CI/CD systems and test pipelines (Jenkins, GitHub Actions, etc.). Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker). Familiarity with databases, monitoring, and observability tools. Strong understanding of SDLC, Agile methodologies, and release processes. Excellent problem-solving, debugging, and communication skills. Preferred qualifications Experience validating ML outputs using statistical analysis or scenario-based testing approaches. Familiarity with ML infrastructure, data pipelines, or model-serving platforms (Seldon, KServe, Ray Serve, etc.). Prior work in content moderation ML, security, fraud detection, or adversarial ML. Experience testing high-scale, low-latency online services. Experience with Databricks or similar ML platform tooling. Familiarity with Node.js, React, or modern frontend technologies. Experience testing mobile, console, or other non-PC platforms. What sets you apart Strong combination of automation engineering and delivery ownership. Ability to drive quality across complex cross-functional initiatives. Practical understanding of how to test non-deterministic AI systems and separate model variance from quality regressions. Proven risk management and dependency coordination skills. Ability to influence engineering teams and promote quality guidelines. Passion for scalable, reliable, and maintainable automation systems. 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. $152,500 — $228,700 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: The Netherlands Workplace: Remote ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - Developer Experience: Design and implement developer tools, SDKs, and documentation that enable users to leverage ClickHouse’s AI/ML capabilities. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Backend development experience in TypeScript or Python, with a focus on API design and service architecture - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus #LI-Remote PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Germany Workplace: Remote ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - Developer Experience: Design and implement developer tools, SDKs, and documentation that enable users to leverage ClickHouse’s AI/ML capabilities. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Backend development experience in TypeScript or Python, with a focus on API design and service architecture - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus   #LI-remote PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Armenia; Spain; Serbia; Poland; Kyiv City; Kyiv; Odesa; North Macedonia Workplace: remote About Provectus Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.   Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.   Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX, Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for . Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire:   Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant  HR Interview. Soft skills and expectations HM interview. Tech questions; a live engine

Location: Warsaw, Poland Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: • Unique opportunity for a career in a global, fast-growing company. • Attractive remuneration package based on qualifications and experience. • Opportunities to learn and grow through our “Employee Training & Development program”. • Hybrid work flexibility. • Multiple events to bond with the team and the group. • Birthday and loyalty benefits. Make your next career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: The Netherlands Workplace: Remote ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders - Strong frontend skills with TypeScript/JavaScript and React Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus - Experience building data-oriented interfaces and visualizations #LI-remote PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.