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Location: Ukraine 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 (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: Colombia; Ukraine; Poland; Brazil; Argentina; Georgia 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. We are seeking a highly skilled and consultative Senior Data Engineer with Databricks expertise to join our team. What you'll do As a Data Engineer, you will provide technical leadership and guide customers to successful implementations of big data projects, ranging from architecture and design to data engineering to model deployment. You will lead clients through migrations and architect solutions from concept to production. You will provide structured mentorship for other team members and technical support for pre-sales efforts. What you bring - Experience leading design and end-to-end development of distributed Databricks-based solutions, including Lakehouse architectures, ETL pipelines, streaming and batch processing, and integration with client's cloud and on-premises enterprise systems. - Hands-on experience in building big data pipelines. - Hands-on programming experience in Python. - Expert knowledge of SQL, Spark (or PySpark), including data ingestion from a variety of sources such as APIs, relational databases, etc. - Hands-on experience using dbt within Databricks ecosystem. - Solid understanding of data governance, security, and compliance. - Hands-on experience with platform optimization: cluster configuration, partitioning strategies, caching, autoscaling, and job orchestration. - Ability to clearly articulate core Databricks concepts and explain their practical applications. - Bachelor's degree in computer science, Information Systems, Engineering, or equivalent work experience. - Databricks Certification (highly desirable) Nice-to-have - Experience with DevOps using Terraform. - Experience with design and deployment of scalable machine learning pipelines on Databricks using MLflow and Delta Lake. - Experience with Azure, AWS or GCP Databricks deployment. - Experience with Databricks deployments for government clients. - Experience with development of interactive dashboards and reports using BI tools, such as Power BI. - Programming experience with Scala. 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.

Location: Islamabad, Pakistan; Punjab, Pakistan; Karachi, Pakistan Workplace: remote At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Data Architect to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Role Summary: The Data Architect will design and govern the complete data ecosystem for the ValueX platform — including data ingestion, processing, modeling, storage, orchestration, and governance. They will define the data architecture blueprint supporting the system’s core modules. 1. Customer Segmentation 2. Business Decisioning & Offer Assignment Engine 3. Real-Time Offer Orchestration Module (ROOM) 4. ML/AI Model Management & Simulation Engine The architect will ensure scalability to handle 50 million+ customer profiles, real-time event streams, and ML-driven decisioning — with a focus on performance, cost optimization, and maintainability. Key Responsibilities: Data Architecture & Design Define the end-to-end data architecture across batch, streaming, and real-time layers. Design Customer 360 and Offer 360 data models, including feature store and historical layers. Establish logical, physical, and semantic data models to enable segmentation, scoring, and orchestration. Define data contracts for Kafka topics, API payloads, and Adobe/CDP integrations. Set up data versioning and lineage frameworks to track data provenance Data Ingestion & Integration Architect data ingestion pipelines from multiple telco sources: OCS, CRM, Kenan, Billing, DWH, Adobe AEP, Pricefx, and external APIs. Define patterns for real-time event ingestion (recharge, offer purchase, balance check). Standardize data access through APIs or data products for downstream modules. Design connectors for cloud storage (e.g., S3, Delta Lake) and integration middleware (e.g., n8n, DecisionRules.io , KNIME). Data Management & Governance Define and enforce data quality, lineage, catalog, and access policies. Establish metadata management frameworks (e.g., DataHub, Collibra, Amundsen). Set up data validation and DQ frameworks (Great Expectations, Deequ). Govern data partitioning, schema evolution, retention, and archiving strategies. Ensure compliance with data privacy and regulatory standards (e.g., PDPA, GDPR, local telecom data policies). Scalability, Cost & Performance Design for high performance and cost-efficient scalability (25M → 50M → 75M customers). Optimize compute/storage balance across environments (Dev, UAT, Prod). Define data lakehouse optimization strategies (Z-Order, Delta caching, compaction). Monitor and manage query performance, cluster sizing, and job orchestration costs. Collaboration & Governance Work closely with Data Engineers, Data Scientists, and Application Developers to ensure architectural alignment. Lead architecture review boards and maintain data design documentation (ERD, flow diagrams, schema registry). Serve as technical liaison between business stakeholders, data teams, and platform vendors (Databricks, Adobe, Pricefx). Provide best practices and design patterns for model deployment, retraining, and data lifecycle management. 10+ years in Data Architecture and Data Platform Design Data Architecture-Data lakehouse design, data modeling (dimensional, normalized, semantic), schema management. ETL/ELT & Orchestration-Databricks, Snowflake, dbt, Airflow, AWS Glue, Azure Data Factory. Streaming & Real-Time-Apache Kafka, Spark Streaming, Kinesis, Flink Data Modeling-Customer 360, Offer 360, Transaction 360, Feature Store Cloud Platforms-AWS (S3, Glue, Lambda, EMR), Azure (ADF, Synapse), or GCP (BigQuery, Dataflow) Storage & Compute-Delta Lake, Parquet, Iceberg, Snowflake Data Quality & Governance-Great Expectations, Deequ, DataHub, Collibra Programming & Scripting-Python, SQL, PySpark, YAML API & Integration Design-REST, GraphQL, Kafka Connect, JSON schema Security & Compliance-IAM, encryption (KMS), access control, masking, PDPA compliance Preferred (Nice-to-Have) Telecom industry experience (recharge, balance, offer, churn, usage data). Experience integrating with Adobe Experience Platform (AEP) or Pricefx. Knowledge of DecisionRules.io , KNIME, or n8n for workflow orchestration. Familiarity with AI/ML pipelines and MLOps frameworks (MLflow, SageMaker). Exposure to knowledge graphs (Neo4j, GraphFrames) for segmentation and recommendation. Educational Background Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related fields. Certifications in AWS/Azure Data Architect, Databricks Certified Data Engineer, or Snowflake Architect are preferred.

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. The successful candidate will join QRT’s growing Compliance Technology function, which sits within the global Compliance team. You will work alongside the business, Compliance and Technology teams to develop and maintain systems supporting market surveillance, regulatory reporting and other compliance processes in a fast-paced and collaborative environment. Market surveillance will be a key focus, with opportunities to contribute to wider projects across the team. Your Future Role within QRT: Develop and maintain Compliance Technology systems and controls, with a focus on market surveillance. Work with stakeholders to understand requirements and translate them into technical solutions. Build and maintain data pipelines and integrations across trading systems, internal platforms and external vendors. Develop automated controls to ensure data completeness, accuracy and timeliness. Support the day-to-day operation of existing systems, investigate production issues and implement lasting fixes. Work with Compliance to implement and test surveillance scenarios and develop tools that support alert review and investigations. Identify opportunities to automate processes and improve system performance and reliability. Own testing and release processes for technical changes, coordinate user acceptance testing and maintain system documentation. Collaborate with developers and stakeholders on wider Compliance Technology projects as priorities evolve. Your present skillset: At least eight years of software development experience, with strong Python and SQL skills. Experience designing and building applications, frameworks and tools from requirements through to production support. Understanding of financial products, including derivatives, and the order and execution lifecycle. Experience building data pipelines, integrating systems and implementing data quality controls. Experience in data modelling. Strong software engineering fundamentals and practical judgement, with the ability to design, write and troubleshoot code independently. Experience using AI-assisted development tools, with responsibility for reviewing, testing and maintaining the resulting code. Strong analytical and problem-solving skills, with the ability to investigate complex technical issues. Ability to communicate clearly and work effectively with technical and business stakeholders. Intellectual curiosity and willingness to learn new technologies and contribute across different areas of the team. Experience with market surveillance platforms, such as Nasdaq SMARTS, or regulatory reporting systems would be an advantage. Experience with big data tools, such as PySpark, would be an advantage. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Москва Отдел исследования данных Управления Комплаенс ищет Руководителя направления по исследованию данных. Основной задачей будет развитие ML моделей для процесса выявления и расследования случаев легализации доходов, полученных преступным путем. Используются различные платформы исполнения моделей – онлайн (в момент проведения операции) и пакетный расчет по всей клиентской базе. Применяем ансамбли моделей градиентного бустинга, нейросетевые архитектуры на последовательностях событий, временных рядах, графовых структурах данных. Обязанности * Декомпозировать задачи и управлять сроками их выполнения; * Собирать выборки для обучения и валидации моделей; * Проверять различные модели для решения задачи (классификация, регрессия, выявление аномалий), выбирать лучшую модель; * Формировать требования к витринам для команды инженеров; * Проводить ревью кода; * Подготавливать презентации для защиты результатов; * Анализировать результаты мониторинга работы моделей на проме; * Участвовать в собеседованиях кандидатов. Требования * Профильное высшее образование; * Хорошее знание теории вероятностей и статистики; * Знание Python и основных библиотек (numpy, pandas, scipy, sklearn); * Уверенное владение популярными алгоритмами машинного обучения и библиотеками градиентного бустинга (LightGBM, CatBoost и др.); * Опыт разработки и внедрения нейронных сетей на PyTorch. * Умение обрабатывать большие объемы данных на PySpark; * Кейсы применения нейросетевых моделей в задачах NLP, Time Series, Graph; * Опыт наставничества или руководства командой. Условия * Бесплатные фитнес залы в офисе; * ДМС с первого дня и льготное страхование для близких; * Выгодная ипотека для каждого сотрудника и льготные условия кредитования; * Скидки на продукты компаний-партнеров; * Онлайн курсы в Виртуальной школе Сбера и обучение в Корпоративном университете; * DS&AI community - регулярный обмен знаниями, опытом и лучшими практиками, интерактивные лекции и мастер-классы от ведущих ВУЗов и экспертов технологических компаний.

Workplace: remote Location : Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities : Review mapping definition with data analysts Contribute with other data scientists on mapping definition for transformation pipelines Contribute to mapping function development and unit testing of these functions Contribute to mapping configurations Define the design of quality control pipelines, ensuring mapping accuracy and alignment with analytical expectations Review and maintain the quality control pipelines with the Data Analyst, Data Domain Lead and Data Governance Lead Implement or configure the appropriate tools for the approved quality control pipelines Provide the guidelines for introducing Machine Learning and LLM in the transformation pipelines What we expect : 10+ years of experience in Data Engineering Strong familiarity with the Databricks platform (including Unity Catalog) Ability to write robust code with Python Proficiency with Spark (PySpark) Knowledge of cloud platforms: AWS Experience in implementing ML and LLM in production data pipelines Ability to collaborate closely with Central European time zone Nice to have : Knowledge of Lakehouse concept including experience using Delta Lake optimized storage layer Familiarity with SODA is a plus We offer : Competitive compensation Remote or office work Flexible working hours Healthcare benefits: medical insurance and paid sick leave Continuous education, mentoring, and professional development programs A team with an excellent tech expertise Certifications paid by the company

Workplace: remote Location : Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities : Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from diverse data generation sources and systems (e.g., lab systems, MES, clinical supply, quality systems, external partners). Create and optimize data flows for structured and unstructured data using Python (PySpark), R, SQL, Databricks, Snowflake, and other modern engineering tools. Develop and maintain specific data repositories, implementing enterprise‑level data models, and creating new models as needed. Enable AI/ML readiness by ensuring data is well‑structured, versioned, traceable, and semantically aligned with enterprise data standards. What we expect : Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred. 6+ years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment. Proficiency with Python, R, SQL, and cloud-based architectures (AWS services, Snowflake, Databricks, Redshift) along with Spark and dbt. Proficiency in RDS Expertise in ETL and DWH. Experience with NoSQL and graph databases. English language proficiency of B2+ Strong analytical, problem‑solving, and stakeholder‑management skills, with the ability to translate discussions into actionable requirements. Ability to drive multiple exciting projects simultaneously with strong organizational skills and adaptability. Nice to have : Experience working with the histopathology domain Experience with regulated or standards‑driven data environments, such as CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards. Familiarity with high‑dimensional data (e.g., imaging, sensor data, etc). Experience with principles connecting to or feeding MLOps and model deployment workflows. Knowledge of manufacturing systems (MES), laboratory information systems, or industrial data systems. Exposure to knowledge graph or ontology‑driven architectures. We offer : Competitive compensation Fully remote work Flexible working hours Continuous education, mentoring, and professional development programs A team with an excellent tech expertise