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Задачи: - Проектирование и разработка продакшн-систем с использованием Python 3.12+ для AI-агентов и LLM моделей - Реализация мультиагентной архитектуры: интеграция компонент, реализация пайплайнов и кастомных оркестраторов (LangChain, LangGraph, RAG) - Разработка и поддержка API (FastAPI, Django): создание микросервисов, REST, асинхронные сервисы - Интеграция с реляционными, NoSQL и векторными базами данных (PostgreSQL, Redis, MongoDB, VectorDB: ChromaDB, QDrant) - Создание, обучение и внедрение ML-моделей (ML pipeline, Prompt Engineering, RAG, оценка качества, A/B тестирование) - Контейнеризация (Docker, Docker Compose) и деплой в Kubernetes, частичная настройка DevOps-процессов (CI/CD: Jenkins, ArgoCD) - Разработка unit-тестов, код-ревью, оптимизация производительности, обеспечение безопасности - Взаимодействие в Agile-командах, участие в планировании, менторинг Требования: - Владение Python 3.12+: глубокое знание стандартных и современных возможностей языка (asyncio, typing, dataclasses, pydantic, pytest) от 4-6 лет - Практический опыт разработки AI/ML решений с использованием LangChain, LlamaIndex, RAG, интеграция с LLM API - Опыт проектирования и сопровождения высоконагруженных REST API на FastAPI/Django (архитектура, DI, сериализация, OpenAPI) - Продвинутая работа с PostgreSQL/Redis, проектирование сложных схем, индексация, оптимизация, векторные базы данных - Навыки контейнеризации, деплой в Kubernetes - Опыт внедрения CI/CD пайплайнов, мониторинга, алертинга, организации логирования - Уверенное знание Git, опыт командной работы (Agile, Scrum) - Английский B2+ для чтения документации и коммуникаций Будет плюсом: - Fine-tuning и кастомизация LLM, prompt engineering, оценка качества - Опыт с MLOps, LLMOps и мультирегиональными архитектурами - Участие в R&D или open-source проектах, менторство, архитектурное мышление - Работа с GigaChat API Условия: - Возможность профессионального и карьерного роста в компании, возможность поучаствовать в разных проектах - Опыт работы в распределенной команде профессионалов - Уровень заработной платы обсуждается индивидуально - Формат работы: Офис/гибрид г.Москва или Санкт-Петербург.

Location: Hamburg Workplace: Hybrid adjoe builds the technologies behind mobile apps growth and monetization. adjoe Ads is our programmatic in-app advertising platform that seamlessly connects advertisers and publishers through direct integration of our Android and iOS SDKs. Every ad decision happens in under 200ms across 10 million daily users, powered by real-time bidding algorithms and user quality prediction models that match the right ad to the right user at the right moment. 50 Billion Daily Bid Predictions The adjoe Ads Data Science team owns the entire bidding algorithm that decides which ad you are most likely to enjoy from start to finish: conversion prediction, user quality estimation, and bid shading. Every bid adjoe placed in an ad auction is the output of ML models making 50 billion predictions daily, trained on data from our mobile SDKs that capture real user behavior at scale. The team moves fast: new ideas tested offline, A/B tests launched in production within minutes. We rely on industry-proven state of the art technology, adapted to our needs and self-hosted where it matters: PyTorch and TensorFlow for modeling, Trino and Athena for querying a 350TB Iceberg data lake, Airflow and Ray for orchestrating our different training pipelines across multiple GPU clusters. Models are built on 600+ features and trained on 200 million data points, with the full ML lifecycle owned by the team from research and experimentation to deployment and real-time inference at sub-200ms latency. Your Mission & Who We Are Looking For: - 5+ years in Data Science, 2+ in leadership. You have a track record of architecting and deploying ML solutions, recommender systems and neural networks specifically, and have led data science teams through hiring, mentoring, regular 1-1s, and career development. At adjoe Ads, you'll be growing and managing the team of Data Scientists, Data & ML Engineers, Data Analysts that owns the entire bidding algorithm. - At least 50% hands-on. This is not a purely managerial role. You work on data science tasks yourself, own critical procedures like experiments and implementation details, and mentor data scientists in advanced modeling, programming quality, and strategic thinking. - Fluent in data at scale. You've worked with large, diverse data sources AWS Athena, Kafka, Spark, Flink, S3, MySQL and know how to extract signals from a 350TB data lake. Strong Python required; experience building an MLOps stack with Airflow, Spark, or Flink is a strong plus. - Bridges math and business. You can dive deep into mathematical foundations and translate complex model behavior into clear decisions for product and business stakeholders. You align with the adjoe Ads product team and Cloud Infrastructure on priorities, tools, and best practices. - Contributes to the roadmap, not just the backlog. You work on long-term strategy and quarterly OKRs, contributing to adjoe Ads' position as a strong competitor in the programmatic adtech market. 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

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.

Задачи: — анализ банковских и крипто-транзакций для выявления мошенничества и AML-сценариев — разработка и улучшение ML-моделей для fraud detection — graph analysis / Graph ML (GNN, node embeddings, link prediction) — вывод моделей в production Требования: — опыт работы с transactional fraud / AML от 5 лет — strong Python + ML stack (PyTorch / TensorFlow) — опыт с Graph ML / Neo4j / NetworkX / GNN — production ML и ETL pipelines Будет плюсом: — MLOps — ClickHouse / Elasticsearch / Cassandra — опыт с real-time systems и асинхронным Python Условия: — релокация (Узбекистан / Дубай / ЕС) или B2B outside РФ/РБ/Украины — зарплата в валюте — relocation package — международная русскоговорящая команда — сложные ML/AI задачи и сильная technical culture

Location: India; Pakistan; Philippines About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are seeking a skilled and innovative Remote AI Engineer with experience in machine learning, large language models (LLMs), and AI application development. You will work closely with product managers, software engineers, and data teams to design intelligent systems, develop AI-powered features, and improve model performance across various applications. This is an exciting opportunity for someone passionate about artificial intelligence, automation, and scalable software development. Key Responsibilities Design, develop, and deploy AI and machine learning models for production environments. Build AI-powered applications using LLMs such as GPT, Claude, Gemini, or open-source models. Create and optimize prompt engineering workflows for generative AI applications. Develop APIs and backend systems that integrate AI services into web and mobile applications. Fine-tune models and improve inference performance, latency, and scalability. Work with structured and unstructured datasets for model training and evaluation. Collaborate with cross-functional teams to translate business needs into AI solutions. Implement vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. Monitor AI system performance and continuously improve reliability and accuracy. Stay updated with the latest advancements in AI, machine learning, and automation technologies. Requirements 3+ years of experience in software engineering, machine learning, or AI development. Strong proficiency in Python and modern AI/ML frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face. Experience working with OpenAI APIs, Anthropic, Gemini, or similar AI platforms. Familiarity with LLMs, RAG architectures, vector databases, and prompt engineering. Experience building REST APIs and scalable backend systems. Knowledge of cloud platforms such as AWS, GCP, or Azure. Understanding of CI/CD pipelines, Docker, and cloud deployment workflows. Strong problem-solving and analytical thinking skills. Excellent communication skills and ability to work independently in a remote environment. Bachelor’s degree in Computer Science, Engineering, AI, Data Science, or related field preferred. Experience deploying AI agents or autonomous workflows. Familiarity with MLOps tools and AI monitoring systems. Experience with Pinecone, Weaviate, FAISS, or ChromaDB. Knowledge of frontend frameworks such as React or Next.js is a plus. Previous experience in SaaS or startup environments. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: United Kingdom; Canada; United States About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a skilled AI Engineer with at least 2 years of hands-on experience in developing, deploying, and optimizing AI and machine learning solutions. You will work closely with product, engineering, and data teams to design intelligent systems, integrate AI models into production environments, and contribute to cutting-edge AI initiatives. This is an exciting opportunity for someone passionate about machine learning, generative AI, LLMs, automation, and scalable AI infrastructure in a fully remote environment. Key Responsibilities Design, build, and deploy AI/ML models for real-world applications. Develop and optimize AI-powered features using modern frameworks and APIs. Work with Large Language Models (LLMs) such as GPT, Claude, or open-source alternatives. Build AI pipelines for data processing, training, inference, and monitoring. Collaborate with cross-functional teams to translate business needs into AI solutions. Integrate AI services into web applications, SaaS platforms, and internal tools. Fine-tune and evaluate machine learning models for performance and scalability. Maintain documentation and ensure AI systems follow security and compliance best practices. Stay updated with the latest advancements in AI, machine learning, and automation technologies. Requirements 2+ years of experience as an AI Engineer, Machine Learning Engineer, or similar role. Strong experience with Python and AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, or LangChain. Experience working with LLMs, generative AI, prompt engineering, or AI agents . Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG). Experience deploying models using cloud platforms like AWS, Azure, or Google Cloud. Understanding of APIs, microservices, and backend development. Experience with Docker, Git, and CI/CD workflows. Strong analytical and problem-solving skills. Excellent communication skills and ability to work remotely with global teams. Bachelor’s degree in Computer Science, AI, Data Science, or related field preferred. Experience with AI automation tools and agent frameworks. Knowledge of MLOps and model monitoring tools. Familiarity with NLP, computer vision, or recommendation systems. Experience building AI SaaS products or chatbots. Exposure to FastAPI, Node.js, or React-based applications. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: South Africa; Pakistan; Philippines; United States; United Kingdom; Canada About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a highly skilled AI Engineer to design, build, and deploy AI-driven applications and machine learning solutions. You’ll work closely with product, engineering, and data teams to create intelligent systems that improve automation, customer engagement, and operational efficiency. This role is ideal for someone passionate about artificial intelligence, large language models (LLMs), machine learning infrastructure, and production-grade AI systems. Key Responsibilities Design, develop, and deploy AI and machine learning models for real-world applications. Build and optimize AI-powered tools using technologies such as OpenAI, Claude, Gemini, or open-source LLMs. Develop scalable APIs and backend services for AI applications. Fine-tune machine learning models and improve model performance. Work with structured and unstructured datasets for training and inference. Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines. Integrate AI solutions into web platforms, CRMs, and business systems. Monitor AI model performance, reliability, and scalability in production. Collaborate with cross-functional teams to define AI product requirements and technical roadmaps. Stay updated on emerging AI technologies, frameworks, and best practices. Requirements 3+ years of experience in AI engineering, machine learning, or software engineering. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face. Experience working with LLMs, generative AI tools, and prompt engineering. Familiarity with vector databases, embeddings, and RAG architectures. Knowledge of cloud platforms such as AWS, GCP, or Azure. Experience building REST APIs and scalable backend systems. Understanding of MLOps, model deployment, and monitoring workflows. Strong problem-solving and analytical thinking skills. Excellent communication and collaboration abilities. Experience working in remote or distributed teams is a plus. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: Colombia; Brazil; Argentina Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. What you will do - Deliver end-to-end data science projects using classical machine learning (e.g., regression, classification, time series forecasting) and deep learning approaches — from data exploration and modeling to deployment and performance tracking. - Collaborate closely with business stakeholders to identify opportunities and translate them into measurable data-driven solutions. - Present complex analytical findings in a clear, actionable way to both technical and non-technical audiences. - Contribute to analytical planning and ensure alignment with overall business objectives. - Support presales activities by preparing data/ML solution concepts, participating in client meetings, and estimating project scope and potential value. - Help shape the Data Science practice by contributing to its strategic development and supporting recruitment initiatives. What you bring - Proven experience as a Data Scientist delivering end-to-end projects — from exploratory data analysis to model deployment, performance evaluation, and experimentation (e.g., A/B testing). - Strong expertise in working with tabular and time-series data, including EDA, feature engineering, predictive modeling, and model evaluation. - Proficiency in Python and common data-science libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch). - Experience leading or mentoring analytics teams and coordinating with business stakeholders. - Excellent communication skills, able to translate between technical and business perspectives effectively. - Solid understanding of business processes and data structures. - Confidence in client-facing settings: gathering requirements, shaping analytical roadmaps, and delivering measurable business value. - Fluency in English for meetings with international clients. Nice to have - Hands-on experience with deep learning, computer vision, or generative AI projects. - Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tools. - Experience with data visualization or BI tools for communicating insights. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Задачи: — Улучшать стабильность и качество текущих AutoML алгоритмов, оптимизировать код; — Разрабатывать новые сценарии платформы для аналитиков (поиск аномалий, очистка данных, кластеризация, анализ дрейфа данных/концепта); — Улучшать отчетность и артефакты по полученной модели (отчёт по модели с интерпретацией LLM, графики, таблицы); — Обновлять документацию и технические инструкции по сценариям платформы; — Взаимодействовать по внедрению новых сценариев и фич платформы с MLOps командой; — Проводить анализ потребностей аналитиков, формализовать их в сценарии; — Поддерживать пользователей (аналитиков); — Отвечать за релизный цикл библиотеки; — Проводить ревью PR от других DS. Требования: — Опыт в Data Science от 3 до 5 лет (важна насмотренность к кейсам и разным моделям, опыт промышленной разработки); — Уверенное владение ML- и DL-стеком Python: PyTorch, LightGBM / XGBoost / CatBoost, Scikit-Learn, Pandas, NumPy; — Умение работать с инструментами: Spark, Hadoop, Hive, MLflow, Airflow / Argo Workflows; — Обязателен опыт в табличных данных и классическом ML (градиентный бустинг, логистическая регрессия, кластеризация); — Будет большим плюсом: Контрибьют в ML-библиотеки; Опыт full-stack разработки; — Не подходят кандидаты с чистой карьерой в CV / NLP / LLM без серьёзного бэкграунда в таблицах. Условия: — Работа в аккредитованной IT компании; — Формат работы: удалённый по РФ (или гибрид — на выбор); — Расширенный ДМС (со стоматологией); — Выдача необходимой для работы техники (ноутбук); — Возможность воспользоваться реферальной программой: «Приведи товарища»; — Участие в Бонусной программе; — Помощь с ипотекой и другими пособиями; — Возможность построить карьеру в рамках ведущих компаний России.

Location: Athens Workplace: Hybrid About the company: KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe. About the role: We are looking for an ML Team Lead to join Kiefer Tech and lead our ML Engineering team. In this role, you will lead the development and continuous improvement of Sophea AI, our Greek-focused Large Language Model. You will work across LLM training, fine-tuning, ASR, inference optimization, model validation, and production-grade ML systems. Beyond the model itself, you will help shape the ML Engineering function at Kiefer Tech: define clear ownership, strengthen team workflows, raise technical standards, and ensure complex ML initiatives are delivered with accountability, clarity, and strong execution. What you will do: - Lead the ML Engineering team working on Sophea AI and set a clear technical direction for its development - Own delivery across core ML workstreams, including LLM training, fine-tuning, ASR, inference optimization, model validation, and production-grade ML systems - Build a stronger operating model for the ML function: improve workflows, clarify ownership, strengthen decision-making, and remove execution blockers - Turn the ML roadmap into clear priorities, accountable workstreams, and measurable outcomes aligned with product and business goals - Mentor ML engineers, develop team capabilities, and bring stronger engineering practices, tools, and research-driven approaches into the team’s daily work What you will need: - Proven experience leading ML Engineering teams or complex ML workstreams in high-performance, fast-moving environments - Deep technical background in LLMs, ASR, and production-grade ML systems, including pre-training, training from scratch, fine-tuning, reinforcement learning, model validation, and performance improvement - Strong understanding of inference optimization, model quantization, and serving frameworks such as vLLM, SGLang, NVIDIA Triton, NVIDIA Dynamo, or similar tools - Ability to bring structure into ambiguous environments: clarify ownership, improve workflows, and drive execution across several ML workstreams - High autonomy, strong communication skills, and the ability to follow current AI research and translate relevant tools, methods, and trends into team practice Nice to have: - Experience with MLOps infrastructure, model serving pipelines, GPU workload management, and experiment tracking - Contributions to open-source ML projects or published research in AI/ML - Familiarity with real-time inference systems or event-driven ML architectures What is there for you: - Compensation: highly competitive package aligned with AI talent benchmarks across Europe and the US - Ownership: high-impact leadership role with real influence on the ML Engineering function at Kiefer Tech - Work format: remote work option, with relocation support available for candidates open to working from our Athens office - AI-native environment: real challenges across LLMs, ASR, GPU workloads, and advanced AI product development - NVIDIA ecosystem: access to related conferences, certifications, internal knowledge sharing, and advanced AI infrastructure through Kiefer’s strategic collaboration - Culture: engineering-first, high autonomy, low bureaucracy, and space to shape meaningful AI products

Location: Morocco We are looking to hire passionate Senior AI Engineers to help turn data into intelligent, production-ready solutions. You will work across the full AI stack: traditional machine-learning models, large language models (LLMs), computer-vision pipelines, and analytics / forecasting workflows. If you enjoy exploring data, building state-of-the-art models, and shipping reliable AI services, we would love to meet you. Responsibilities Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion). Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs. End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring. LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements. AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines. Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team. Mentor junior engineers and contribute to technical direction and engineering best practices. Requirements BSc in Computer Science, Mathematics, or related field. 5+ years of professional experience working on AI/ML projects. Good command of English and Arabic (written and spoken). Proficient in Python and core libraries (PyTorch / TensorFlow, scikit-learn, pandas, NumPy). Solid understanding of machine-learning algorithms, deep-learning fundamentals, and basic statistics. Experience with data wrangling and visualization (Matplotlib / Plotly) and exploratory analysis. Familiarity with at least one of: OpenCV, Hugging Face Transformers, LangChain, MLflow, or similar. Good grasp of software-engineering best practices: Git, code reviews, testing, CI. Preferred Qualifications Knowledge of C++ or C# for performance-critical modules. Experience deploying models via Docker, Kubernetes, or cloud AI services. Exposure to vector databases and RAG workflows. Skill in BI / dashboard tools (Power BI, Tableau, Streamlit) or time-series frameworks (Prophet, statsmodels). Familiarity with MLOps / LLMOps tooling (DVC, MLflow Tracking, Weights & Biases, BentoML). Experience with image processing techniques (e.g., OpenCV, image segmentation, feature extraction) Experience with Spark (PySpark) and distributed data processing, including usage of platforms such as Databricks, AWS EMR, or GCP Dataproc. Strong SQL skills and experience working with large-scale datasets, including partitioning and performance tuning. Familiarity with modern data lake architectures and scalable data storage concepts.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London. WHAT YOU’LL DO - Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. - Build and maintain robust CI/CD pipelines for both software and ML workflows. - Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. - Automate deployment, orchestration, and environment management using modern DevOps tooling. - Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. - Proactively detect, troubleshoot, and resolve infrastructure and model performance issues. - Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering. - Document infrastructure, workflows, and operational procedures clearly and thoroughly. WHAT WE'RE LOOKING FOR - Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. - Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. - Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). - Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm). - Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing. - Ability to design scalable, secure, and observable systems in fast-moving environments. - Strong debugging and problem-solving skills across distributed systems. - Excellent collaboration and communication skills, with experience working in cross-functional teams. - Understanding of security and compliance best practices for both software and ML systems. WHAT WE OFFER - Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. - Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support. - Equity included–we believe builders should share in what they build. - Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.

Location: Home Based - Americas; Home based - EMEA This is an opportunity to run the worldwide Telco Field Engineering business, helping customers understand and implement Canonical's open source solutions in public clouds and in their own data centers. We work across the entire spectrum of cloud offerings, from Ubuntu itself to virtualisation and private cloud, Kubernetes, and the implementation of sophisticated open source solutions such as MLops platforms, data platforms and more. The Telco department is composed of three regional teams (APAC, EMEA and AMER). We believe that Engineering Directors should be outstanding engineers themselves. They should feel completely at home troubleshooting technical issues and having technical presales conversations with customers. They should contribute to project delivery themselves, but know that the technical contributions they bring are far less significant than their ability to shape the whole team’s direction, focus and delivery. We grow management skills and train engineers, who are interested in soft skills, to be managers. We believe that open source is just starting to transform the tech sector and enterprise compute. Our goal is to make open source easier, more reliable and more secure for deployment and development. We strive to be the provider of ‘most software to most companies’. To deliver on that ambition, our engineers are carefully selected from the applicants across the globe. We select for brilliance and motivation to take open source to the next level. Our engineering managers help teams achieve more than they realised they could, and feel proud of the result. The role of a Telco Field Engineering Director at Canonical The Field Engineering department is our team of cloud solutions architects at Canonical, working directly with our customers, designing private and public cloud solutions fitting their workload needs. The portfolio of products includes on-premise cloud solutions such as Openstack, MicroCloud and Ceph, and solutions that could be deployed either on-premises or in public clouds such as Kubernetes, Kubeflow, Spark, PostgreSQL, etc.  The team works hands-on with the technologies by deploying, testing and handing over the solution to our support or managed services team at the end of a project. Managers and team members also take part in presales conversations to provide technical advice during the sales process. Within the Field Engineering department, there are multiple focused teams : the Cloud/DC team, the Alliances/Partners team, the IoT team, and the Telco team. The telco industry is moving to software-defined services. This transformation is driven by open source software, cloud computing and the move to VNF / CNF approaches. Canonical Ubuntu is a key platform for telco innovation, and we are growing our team of specialists who work in the industry to accelerate the change. Canonical enables operators and communications service providers to embrace this new world, with a focus on platforms such as Ubuntu, OpenStack, and Kubernetes, and reusable, high quality automation for operations at scale. A Cloud Field Engineering Director is responsible for driving the strategy in presales and delivery for our telco customers. The ability to develop engineering talent, to represent your team from a technical perspective, and to drive collaboration with other teams and customers are all critical to success in this role. You are also expected to actively participate in technical presales to help our department achieve our quarterly goals. Location: This role will be home based, managing teams in worldwide. What your day will look like Lead and develop managers and teams of Field engineers in the areas of Presales and Professional Services Solve customer problems by promoting our technologies and being a trusted advisor Work remotely in a single major time zone Coach, mentor, and offer career development feedback Identify and measure team health indicators Implement disciplined engineering processes Represent your team and product to stakeholders, partners, and customers Develop and evangelise great engineering and organisational practices Plan and manage progress on agreed goals and projects Be an active part of the leadership team, collaborating with other leaders What we are looking for in you A thorough technical understanding of the telco NFVi (VIM), NFVO, VNFM and MEC space and key telco cloud infrastructure technologies like CPU Pinning, NUMA, SR-IOV, DPDK, etc Familiarity with telco architecture and industry standards Working knowledge of at least one of the following domains: Mobile Packet Core (4G/5G), Private Network, Radio Access Network (RAN), Voice, IP Backbone, VAS or OSS/BSS Knowledge of cloud computing concepts & technologies, such as Kubernetes, Openstack, AWS, GCP, Azure, Ceph, etc. Practical knowledge of Linux and networking Experience in technical presales You are a dynamic person who loves to jump in new projects and interact with people Excellent verbal and written communication skills in English Passion and a track record of developing and growing people Experience in leading, coaching and mentoring engineers and managers Organised and able to ensure your team delivers timely, high quality results An exceptional academic track record from high school and, preferably, university as well Willingness to travel up to 25% of the time. Field Engineers attend internal company events, external tech events and customer meetings. Additional skills that you might also bring Second language - Spanish or French preferred Python knowledge Experience collaborating with external partners Experience collaborating with several internal teams and providing stakeholder feedback for engineering roadmaps Understanding of AI and machine learning concepts, including sovereign AI, and their potential applications in telco environments, such as network optimization, predictive maintenance, unified communication, and customer experience improvement Exposure to frameworks such as 3GPP, TM Forum ODA, eTOM, ETSI NFV, ONAP, O-RAN, or similar is a plus What we offer you We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally. Distributed work environment with twice-yearly team sprints in person Personal learning and development budget of USD 2,000 per year Annual compensation review Recognition rewards Annual holiday leave Maternity and paternity leave Employee Assistance Programme Opportunity to travel to new locations to meet colleagues from your team and others Priority Pass for travel and travel upgrades for long haul company events About Canonical Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Canonical has been a remote-first company since its inception in 2004.​ Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business. Canonical is an equal opportunity employer We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration. #LI-remote

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. Now we look for a Data Scientist to join our ML team Job Responsibilities Search & Retrieval Develop and improve retrieval pipelines for large-scale production search systems. Work on candidate generation, query processing, matching, filtering, and retrieval strategies. Improve search relevance, result coverage, and overall SERP quality. Analyse failed searches, irrelevant results, zero-result queries, and other search-quality issues. Explore lexical, semantic, behavioural, hybrid, and vector search approaches. Ranking & Relevance Build, train, and optimise ranking models for search and recommendation systems. Develop learning-to-rank solutions using behavioural, content-based, contextual, and real-time features. Design ranking features based on clicks, conversions, popularity, freshness, availability, and user behaviour. Evaluate ranking quality using Precision, Recall, NDCG, MAP, MRR, and related relevance metrics. Optimise models for low-latency inference and investigate relevance degradation, bias, and feedback loops. Recommendation Systems Develop recommendation models and candidate-generation strategies for personalised and non-personalised scenarios. Build recall and ranking stages for multi-stage recommendation pipelines. Work on related-item, complementary-item, next-action, and behavioural recommendation use cases. Develop user, item, session, and contextual representations. Balance relevance, diversity, novelty, coverage, and business constraints. Experimentation & Evaluation Design and run offline and online experiments for search, ranking, and recommendation improvements. Build evaluation frameworks that connect model quality with product and business outcomes. Design and analyse A/B tests using CTR, conversion, engagement, retention, and revenue-related metrics. Create reproducible pipelines for data preparation, model training, evaluation, and comparison. Evaluate model robustness across traffic segments, query groups, user cohorts, and edge cases. ML Pipelines & Collaboration Build end-to-end ML pipelines for feature generation, training, validation, deployment, and monitoring. Work with high-load, real-time, and low-latency production systems. Process large datasets using Python, SQL, batch pipelines, streaming systems, and Kafka. Collaborate with product, backend, data engineering, and MLOps teams to productionise ML solutions. Communicate technical decisions, experiment results, and trade-offs while contributing to ML best practices. You’ll thrive here if you have Strong hands-on experience building production search, ranking, or recommendation systems. Strong Python and SQL skills for machine learning, data processing, and analytical queries. Practical experience with learning-to-rank, candidate retrieval, search relevance, or recommender-system modelling. Experience building and evaluating multi-stage retrieval and ranking pipelines. Strong understanding of search and recommendation metrics, including Precision, Recall, NDCG, MAP, MRR, CTR, and conversion. Experience with feature engineering and behavioural data such as impressions, clicks, sessions, and conversions. Experience with ML libraries such as scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, or TensorFlow. Experience working with large-scale production systems, distributed data processing, analytical databases, and streaming platforms. Strong understanding of experimentation and A/B testing, with the ability to independently build, and validate ML solutions. That can be a plus: Experience with Elasticsearch, OpenSearch, Solr, Lucene, or another search-engine stack. Experience with vector databases, approximate nearest neighbour search, and hybrid lexical-semantic retrieval. Experience with query understanding, classification, spell correction, synonyms, or query expansion. Experience with DSSM, two-tower models, BERT-based ranking, cross-encoders, or similar neural architectures. Experience with large-scale data and ML platforms such as Airflow, MLflow Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR interview (40 min); Technical interview (1.5 hour); Final interview (45 min).

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Team We sit on the front lines of OKX's security and compliance mission. Our charter is to build the flexible, scalable, and intelligent AI systems that detect and prevent identity fraud, account takeover, and large-scale organized abuse — in real time and at the scale of a global financial platform. We own the core identity-risk capabilities that decide, millions of times a day, whether an account can be trusted: identity trust signals, behavioral risk modeling, relationship and cluster intelligence, and face, liveness and document verification. We work shoulder-to-shoulder with Product, Risk, Compliance, and Engineering to turn the hardest adversarial problems in crypto into production-grade defenses that protect good users and the open financial system. About the Role We are looking for a Senior AI Engineer to design, build, and own key identity-risk and trust models at OKX. You will build models that combine identity verification results, device and geo data, and user behavior into trust and risk signals, and use graph and clustering methods to uncover organized, industrialized fraud. This is an end-to-end, research-to-production role: you will own algorithms in your domain and ship models into real-money, high-risk, large-scale production environments. You will be a hands-on technical contributor who works closely with Product, Risk, and Compliance, and who helps raise the technical bar of the team. Your domains span: Identity trust & risk modeling — fusing verification scores, device, geo, and behavioral data into identity-quality and trust signals. Cluster & relationship intelligence — graph and clustering methods to identify account farms, mass registration, and coordinated attacks. Behavioral risk modeling — behavioral features and sequence models for account takeover and abnormal-session detection. Biometric & multimodal signals — face embeddings, liveness/anti-spoofing, DeepFake and injection defense, document forgery and AIGC detection, used as inputs to identity trust and the risk layer. AI agents — applying agentic AI to scale investigation, detection, and operational defense. What You'll Be Doing Build identity trust & risk models: Design and ship coarse-to-fine risk models that fuse face/liveness/document verification scores, device, IP and geo signals, and behavioral data, for high-concurrency real-time decisioning. Uncover organized fraud with graph & clustering: Build entity graphs across accounts, devices, faces, documents and templates, and apply community detection, clustering, and GNN methods to detect fraud rings and large-scale abuse. Develop behavioral features & sequence models: Engineer real-time and offline behavioral features, and build sequence models to detect account takeover, bot/script behavior, and abnormal sessions. Leverage biometric & multimodal signals: Turn biometric features (face embeddings, face quality, liveness and anti-spoofing results) and document-forgery and DeepFake signals into reliable identity-trust inputs for risk decisions, including biometric similarity for cross-account linkage and duplicate-identity detection. Work with the face, liveness, and document teams, or build models yourself. Drive execution & collaboration: Deliver measurable results while managing ambiguity; partner with backend, product, infrastructure, risk, and compliance teams to integrate models into the production decision chain. Own metric definitions, the balance between false positives and missed fraud, pass rate, monitoring, and drift handling. Advance applied R&D: Experiment with graph learning, multimodal fusion, and AI agents; stay current with academic and industry advances and translate them into practical defenses. Raise the technical bar: Contribute to design reviews, share applied-AI best practices, and mentor junior engineers. What We Look For 5+ years of hands-on experience building risk-control, fraud-detection, or identity-trust models, including significant experience deploying ML systems into production. Graph & clustering expertise: Experience applying graph mining, community detection, clustering, or GNN methods to fraud or abuse detection. Behavioral modeling: Solid experience with behavioral feature engineering and sequence modeling, including real-time feature pipelines. Deep AI/ML expertise: Strong proficiency with PyTorch and/or TensorFlow, and solid experience with production ML systems. Strong technical & coding skills: Strong coding ability (e.g., Python, SQL) and the system-level thinking to design end-to-end solutions with high availability and low latency. Adversarial mindset: Understanding of how fraudsters adapt, and how to evaluate and iterate defenses against evolving attacks. Collaboration: Strong communication skills, with experience working across engineering, product, and risk teams. Education: Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field. Preferred Qualifications Experience in identity verification, KYC/KYB, AML, face-payment or payment risk control, or biometric security. Hands-on experience with face recognition, liveness/anti-spoofing, OCR, document parsing, fake-ID detection, or media forensics. Experience with graph databases or graph computing (e.g., Neo4j, GraphX) and real-time graph features. Knowledge of data and AI/ML infrastructure (e.g., Spark, Flink, Kafka, Airflow, Snowflake). Familiarity with MLOps best practices: monitoring, retraining, and continuous improvement of production models. Experience with LLMs and AI agents. Experience working in fast-paced technology companies or security-critical environments. Research publications, patents, or open-source contributions in relevant AI fields. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: Riyadh, Saudi Arabia; Cairo, Egypt; Casablanca, Morocco; Delhi, India; Dubai, United Arab Emirates Müller’s Solutions is excited to announce an opening for a Google Cloud AI Specialist to drive our artificial intelligence initiatives leveraging Google Cloud Platform (GCP). In this role, you will be responsible for designing and implementing AI and machine learning solutions to help transform our data into actionable insights and enhance decision-making processes across the organization. Key Responsibilities: Develop and deploy machine learning models using GCP tools such as AI Platform, TensorFlow, and AutoML. Collaborate with cross-functional teams to identify business needs and translate them into AI and ML project requirements. Conduct data analysis to prepare datasets for model training and evaluation while ensuring data quality and integrity. Implement and optimize AI workflows that facilitate real-time data processing and inference. Stay updated on the latest advancements in AI and machine learning technologies to continuously improve our offerings. Provide technical guidance and support to teams on best practices for using Google Cloud AI services. Document AI project implementations, model performance evaluations, and ongoing maintenance procedures. Contribute to developing educational materials and training sessions on AI capabilities for staff and stakeholders. Monitor and assess the performance of deployed AI models, making adjustments as necessary to ensure effectiveness. Requirements Requirements: Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 3+ years of experience in machine learning or AI solutions development, preferably using Google Cloud Platform. Proficient in programming languages such as Python or R, with a strong understanding of machine learning libraries (e.g., TensorFlow, scikit-learn). Experience with cloud-based AI technologies, especially GCP services like Vision AI, Natural Language API, and AutoML. Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques. Ability to work with large datasets, utilizing BigQuery or similar data processing tools. Excellent problem-solving skills and a strong analytical mindset. Capable of communicating complex technical concepts to diverse audiences effectively. Preferred Qualifications: Google Cloud certifications (e.g., Google Cloud Professional Data Engineer or Google Cloud Professional Machine Learning Engineer) are a plus. Experience with MLOps practices and tools for model deployment and management. Familiarity with DevOps practices as they relate to AI and machine learning. A background in statistics or applied mathematics is desirable. Benefits 1- Attractive Package. 2- Family Benefits. 3- Visa. 4-Air Tickets.

Location: San Francisco; Stockholm; New York; London Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal is hiring a high-impact Solutions Architect to drive technical strategy across our most strategic enterprise accounts. You will operate as the executive technical counterpart to Enterprise Account Executives, leading complex evaluations, shaping infrastructure modernization roadmaps, and driving multi-product adoption across AI/ML workloads. This role is not demo support. It is a strategic, consultative position requiring strong architectural depth, executive presence, and the ability to influence 7–8 figure infrastructure decisions. You will work directly with CTOs, VPs of Engineering, and ML platform leaders to help them rethink how AI infrastructure should be built and operated. If you thrive in high-velocity technical sales environments and want to shape the infrastructure layer powering modern AI companies, this role is for you. WHAT YOU’LL DO: - Own the technical strategy for large, complex enterprise accounts - Partner with Enterprise Account Executives to drive 6–7+ figure opportunities from qualification through close - Lead deep technical discovery across platform, ML, DevOps, and infrastructure stakeholders - Architect end-to-end migration strategies from AWS, GCP, or Azure to Modal’s serverless infrastructure - Drive executive-level technical conversations that connect infrastructure architecture to business impact (velocity, cost efficiency, reliability) - Design and oversee proof-of-concepts that demonstrate production-grade scalability and performance - Navigate security reviews, compliance discussions, and procurement processes with confidence - Build durable relationships with technical champions and executive sponsors - Orchestrate cross-functional virtual account teams (Sales, Product, Engineering, Support) to ensure successful adoption - Influence Modal’s product roadmap by surfacing structured enterprise feedback - Mentor other Solutions Architects and contribute to technical best practices across the team REQUIREMENTS: - 5+ years in Solutions Engineering, Sales Engineering, or enterprise-facing technical roles in infrastructure, cloud, or developer platforms - Demonstrated success driving complex enterprise sales cycles ($250K+ ACV; experience with $1M+ ARR accounts strongly preferred) - Experience working with large, sophisticated Bay Area technology companies or global enterprises - Deep expertise in cloud infrastructure (AWS, GCP, Azure) including compute, networking, storage, and managed services - Strong architectural understanding of containers and orchestration (Docker, Kubernetes) - Experience designing distributed systems and production data platforms - Strong working knowledge of ML/AI infrastructure (training pipelines, inference systems, GPU workloads, MLOps) - Experience leading cloud migration or infrastructure modernization initiatives - Familiarity with Infrastructure as Code (Terraform, Pulumi, CloudFormation) and CI/CD systems - Production programming experience in Python strongly preferred - Executive-level communication skills with the ability to influence technical and business stakeholders - Proven ability to lead cross-functional virtual teams in high-stakes account environments - Strong business acumen and understanding of enterprise procurement and buying processes - Willingness to travel up to 30%

Location: Dhahran, Saudi Arabia; Bengaluru, India Eram Talent, a leading talent acquisition company, is on the lookout for a highly skilled Data & AI Architect to join our team in Saudi Arabia. The Data & AI Architect will be instrumental in designing and implementing data-driven solutions that leverage advanced analytics and artificial intelligence to empower business decisions across various projects in the region. This role requires a deep understanding of data architecture, data modeling, and AI/ML technologies. The architect will collaborate with cross-functional teams to ensure that the data architecture is robust, scalable, and aligned with the business strategies. This position offers an exciting opportunity to innovate and shape the future of data utilization within organizations. Responsibilities Own enterprise data architecture and extend it to AI and MLOps capabilities to enable trusted analytics and scalable AI delivery. Develop and implement a comprehensive data architecture strategy that supports business goals and AI initiatives. Design data models, database structures, and data flow processes to ensure data integrity, availability, and security. Design and oversee the implementation of advanced analytics solutions, including machine learning models and algorithms. Collaborate with data engineering and data science teams to ensure that data pipelines are efficient and aligned with AI/ML requirements. Establish best practices for data governance, data quality, and data lifecycle management. Support the selection and implementation of data management tools and technologies. Engage with stakeholders to understand their data needs and ensure that data solutions deliver maximum business value. Monitor trends in the data and AI landscape, refining strategies as necessary to drive continuous improvement and innovation. Requirements Education: Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field. Experience: 15+ years of experience in data architecture, data engineering, or AI/ML roles. Proven experience in designing and implementing data models and architecture in large-scale data environments. Experience with AI and machine learning frameworks, libraries, and tools. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). Skills: Strong knowledge of database systems (SQL and NoSQL) and data warehousing concepts. Excellent analytical and problem-solving abilities. Strong communication skills, with the ability to convey complex data concepts to non-technical stakeholders. Ability to work collaboratively in a team-oriented environment.