Вакансии

Location: Limassol, Cyprus Workplace: remote Our team is developing a payment gateway for accepting funds from users on behalf of merchants, as well as sending funds from merchants to users. The system involves storing user payment data and is subject to PCI DSS compliance. It contains multiple integrations with payment systems, providers, and other gateways and processors, including 3DS. We're looking for a Payments Data Analyst to join our Product team and transform payment and product data into actionable insights that improve merchant success, platform performance, and business decisions. As a Payments Data Analyst, you will be a strategic partner to the Product, Merchant Solutions, Processor Integrations, and ML teams, helping drive data-informed decisions across our payment platform. You will analyze payment performance, identify trends and optimization opportunities, evaluate the impact of product initiatives, and provide recommendations that improve approval rates, payment efficiency, and merchant experience. Job Responsibilities: Monitor, analyze, and optimize payment performance across merchants, processors, payment methods, and markets. Analyze approval rates, decline patterns, payment routing performance, retry and cascading effectiveness, 3DS performance, and transaction success. Perform deep-dive analyses to identify trends, anomalies, and optimization opportunities across processors, card schemes, BINs, countries, merchants, and payment methods. Measure the impact of new product features, processor integrations, routing changes, payment optimization initiatives, and A/B experiments. Build and maintain dashboards and reports that provide actionable insights for Product, Merchant Solutions, Executive, and other business teams. Define, monitor, and improve key product and payment KPIs. Investigate merchant and processor performance to identify root causes and recommend improvements. Collaborate with Product Managers to support product discovery, feature prioritization, and success measurement. Work closely with Solution Engineers, Integration Analysts, and the ML Specialist to improve payment performance and operational efficiency. Support continuous monitoring of payment performance by identifying anomalies, emerging trends, and opportunities for optimization. Present analytical findings and recommendations in a clear, business-oriented manner to technical and non-technical stakeholders. You’ll thrive here if you have 4+ years of experience as a Data Analyst, Product Analyst, Payments Analyst, or in a similar analytical role. Advanced SQL skills, including complex queries and window functions. Experience with BI tools such as Metabase, Tableau, Power BI, Looker, or similar. Experience with Python (Pandas, Jupyter Notebook) for data analysis. Strong analytical thinking and problem-solving skills. Experience working with large datasets. Ability to translate complex data into clear business recommendations. Nice to Have Experience in FinTech, Payments, SaaS, or E-commerce. Understanding of payment processing, payment orchestration, or PSP integrations. Knowledge of payment routing, retries, cascading, and 3DS authentication. Familiarity with payment KPIs such as approval rate, conversion rate, authorization rate, and decline analysis. Understanding of fraud-related metrics, chargebacks, RDR, and risk signals. Experience working with product analytics, experimentation, and feature adoption metrics. Basic understanding of Machine Learning concepts. Conditions We know that great talent deserves great conditions, so here’s what you can expect when joining us: Full remote work. Competitive compensation with a service contract. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. An annual allowance that you can use for home office improvements, sports activities, equipment upgrades, and more—tailor it to what benefits you most. Investment in your development: paid language courses, access to various learning platforms, and a mindfulness benefit, including psychological support with 50% coverage. Career growth in a fast-scaling project with opportunities to influence technical decisions. A culture of recognition: our peer reward program celebrates contributions from across the team. This opportunity is also available for those who already live in Limassol, Cyprus. EU-based employment contract and a 3-year Cyprus work visa. 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. 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. 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. Benefits are provided in accordance with the company’s policies and eligibility criteria. Recruitment process HR interview (40 min); Technical interview (1 hour); Final interview (1 hour); Recommendations check; Job Offer.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for a Senior Data Scientist to analyze complex airport operational and passenger experience challenges using statistical methods, machine learning, natural language processing, segmentation, and experimental approaches. In this role, you will work closely with product, operations, and engineering teams to identify opportunities, generate actionable insights, and support strategic decision making with data. You will apply advanced analytical techniques to understand problems deeply, validate hypotheses, and guide business prioritization. The Airport Touchpoint domain focuses on enhancing the passenger experience across airport operations, from arrival through boarding, while improving the operational processes that support the journey. This role is centered on deep problem discovery, leveraging statistical analysis, machine learning, natural language processing, segmentation, and exploratory analytics to uncover insights, identify improvement opportunities, and provide data driven evidence for strategic decision making and prioritization. You will transform complex operational and customer experience data into actionable recommendations that drive measurable business impact. Analyze complex business and operational challenges using statistical modeling, clustering, natural language processing, and exploratory data analysis. Generate actionable insights and supporting evidence to guide strategic prioritization across airport teams. Apply advanced statistical techniques including hypothesis testing, inference, and multivariate analysis. Conduct segmentation, clustering, principal component analysis, embeddings, and other dimensionality reduction techniques. Build lightweight machine learning and natural language processing models including topic modeling, classification, and semantic grouping. Design experiments and apply causal inference methodologies to evaluate business impact. Develop reproducible analytical pipelines and datasets using Python and SQL. Create dashboards and visualizations that support executive decision making. Collaborate with Product, Airport Operations, Data Engineers, and other stakeholders to guide strategy through data driven insights. Promote analytical rigor, documentation standards, reproducibility, and data driven decision making practices. 5+ years of experience in Data Science, Applied Analytics, or a related field. Strong foundation in statistics, hypothesis testing, inference, and multivariate analysis. Experience with segmentation, clustering, principal component analysis, and embeddings. Hands on experience with machine learning and natural language processing techniques including topic modeling, classification, and semantic analysis. Strong background in experimental design and causal inference. Proficiency in Python, including Pandas, NumPy, scikit learn, and StatsModels. Advanced SQL skills. Experience building end to end machine learning models and reproducible analytical pipelines. Strong data visualization skills and experience creating decision oriented dashboards. Ability to communicate analytical findings effectively to executive and non technical audiences. Experience collaborating across cross functional teams and influencing decisions through data. Experience working in Agile environments. Fluency in Spanish. Intermediate English for documentation and cross team collaboration. Experience in airport operations or logistics. Familiarity with GCP tools (BigQuery, Dataform, Dataflow, Pub/Sub). Experience scaling analyses and collaborating closely with Data Engineers. Core Competences Analytical curiosity and deep problem understanding. Experimental and impact-oriented mindset. Autonomy, ownership, and critical thinking. Ability to turn complex findings into actionable recommendations. Clear communication with both technical and non-technical teams.

Location: Москва Отдел обеспечения безопасности объектов критической информационной инфраструктуры в поисках эксперта. Обязанности ### Вам предстоит: * автоматизация текущей деятельности, отчетности и аудита * разработка внутренних python-приложений для автоматического сбора данных из банковских IT-систем (BI-платформы, ITSM, CMDB), сопровождение категорирования АС, агрегация данных и вычисление показателей защищенности * проведение внутреннего аудита защищённости * проверка соответствия процессов разработки и эксплуатации информационных систем требованиям регуляторов (ФЗ-187, Указы Президента РФ) * моделирование угроз и оценка рисков * создание детальных моделей угроз согласно методике ФСТЭК, оценка уязвимостей и рисков информационной безопасности. * обеспечением соответствия законодательству (ФЗ-187) * полный цикл управления объектами КИИ: категорирование, отправка сведений во ФСТЭК/НКЦКИ, актуализация моделей угроз после изменений архитектуры сервисов, подготовка отчётной документации для внешних проверок * разработка внутренней нормативно-правовой базы * составление и обновление организационно-распорядительных документов под текущие изменения законодательства * AI-поддержка бизнес-процессов * использование технологий больших языковых моделей (LLM) для автоматизации анализа изменений в законодательстве, составления матриц применимости требований и подготовки аналитических материалов * экспертное сопровождение команд разработки и поддержки * постоянный мониторинг исполнения требований регулятора, консультативная поддержка команд банка по вопросам развития систем в соответствии с законодательством. Требования ### Что для нас важно: * высшее профильное образование в области информационной безопасности * курсы профессиональной переподготовки объемом не менее 504 часов по программам, согласованным ФСТЭК России * опыт практической работы с системой защиты объектов КИИ от двух лет и выше * уверенное владение языками программирования: python (обязателен опыт работы с библиотеками pandas, numpy) * знание фреймворков и инструментов: SQLAlchemy, OpenPyXL, Django/Flask * навыки интеграции с внешними сервисами через RESTful API (SIEM, SOAR, Vulnerability Scanners) * владение инструментами CI/CD и системами контроля версий (Git/GitLab) * практический опыт построения дашбордов и визуализации данных (Power BI, Tableau, Grafana) * глубокое понимание российского законодательства в сфере КИИ (ФЗ-187, Приказы ФСТЭК №235, №239, Указы Президента РФ №166, №250, Постановления Правительства РФ №127, №1912) * способность самостоятельно следить за изменениями в законодательстве и своевременно корректировать внутренние процессы * опыт успешного внедрения решений на основе больших языковых моделей (GPT, BERT и др.) * умение формулировать эффективные промпты для генерации текстов, вычитки документации, создания чек-листов и аналитики * понимание этических аспектов и ограничений применения искусственного интеллекта в вопросах безопасности. Условия ### Мы предлагаем: * комфортный современный офис * офисный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Wrocław, Poland What is Box? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. Why Box needs you: We are looking for a Machine Learning Engineer to design, build, and operate reliable machine learning systems that deliver meaningful product impact at enterprise scale. In this role, you will combine strong software engineering and applied machine learning skills to take solutions from idea through production. You will work closely with engineering, product, data, and infrastructure partners to develop scalable ML and agentic capabilities, improve model quality, and ensure that systems are secure, observable, and dependable for Box customers. The Metadata Extraction team builds AI-powered capabilities that transform unstructured enterprise content into structured, usable metadata. The team works on the platform and machine learning layer of document understanding, developing and operationalizing technologies such as OCR and LLM-based extraction agents. These capabilities help understand document layout, tables, handwriting, semantic content, and other complex information within enterprise documents. As a Machine Learning Engineer, you will build reliable, scalable systems that support the development, evaluation, deployment, and operation of these AI capabilities. You will collaborate with engineers, product partners, and adjacent platform teams to bring document intelligence features to Box customers at enterprise scale. What you'll do: Design, build, deploy, and maintain production LLM agents, machine learning models and services. Develop robust data preparation pipelines, prompt and tool design, and agentic workflows. Write high-quality, maintainable, and well-tested Python code for production systems. Partner with Product, Software Engineering, Data, and Infrastructure teams to translate customer and business needs into ML-powered capabilities. Evaluate and improve agents quality using appropriate offline and online metrics, eval sets, experiments, and feedback loops. Monitor production ML systems for quality, reliability, latency, cost, and data or model drift; investigate and resolve issues as needed. Contribute to the architecture of scalable services and pipelines that support real-time and batch ML workloads. Create clear technical designs, documentation, tests, and operational runbooks. Share knowledge, contribute to engineering best practices, and help raise the bar for code quality and operational excellence. Participate in an on-call rotation and help triage production issues when on call. Who you are: We are an AI-first company. This means you approach your work with a growth mindset and find ways to leverage AI to help make faster, smarter decisions that will 10X your impact at Box. You have 3+ years of experience building, deploying, or operating production software, data, or machine learning systems. You have strong programming skills in Python and are comfortable writing production-grade, readable, testable, and maintainable code. You have practical experience with the LLM based agents lifecycle: data and eval-set preparation, prompting and tool schemas, RAG, evaluation, deployment and monitoring. You have experience with LLM application frameworks and libraries, such as LangChain, LangGraph, PyTorch, Pydantic, Pandas, or NumPy, and are comfortable calling LLM APIs (e.g. Gemini, Claude, OpenAI). You understand core machine learning concepts and can make pragmatic trade-offs between model performance, reliability, latency, scalability, and cost. You have experience building APIs, services, pipelines, or distributed systems in a cloud environment. You are familiar with CI/CD, observability, testing, and production support practices. You communicate clearly with both technical and non-technical partners. You have an ownership mindset, enjoy solving ambiguous problems, and work collaboratively across teams. Nice to have: Experience with MLOps tooling, model monitoring, feature stores, workflow orchestration, or experiment tracking. Experience with generative AI in production: multi-provider gateways, semantic search, or structured extraction. Experience with multimodal intelligent document processing workflows. Experience with a major cloud platform, including GCP, AWS, or Azure, and technologies such as Kubernetes and Terraform. Experience with SQL and large-scale analytics (e.g. BigQuery) for quality, cost, and incident investigation. Experience in enterprise software, security, search and retrieval, or content intelligence. Experience mentoring engineers or contributing to technical direction. Methodology Agile management - Scrum Issue tracking tool -Jira Knowledge repository - GitHubEnterprise Code reviews - GitHubEntreprise Version control system - GIT BENEFITS Check out the overview of Life at Box which include general perks and benefits. Box lives its values, with community and in-person collaboration being a core part of our culture. Boxers are expected to work from their assigned office a minimum of 3 days per week. Your Recruiter will share more about how we work and company culture during the hiring process. At Box, we believe unique and diverse experiences benefit our culture, our products, our customers, our company, and our world. We aim to recruit a passionate, high-performing workforce that reflects the world we live in. If you are head-over-heels about this role but unsure if you meet all the requirements, we encourage you to apply! EQUAL OPPORTUNITY We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation. For details on how we protect your information when you apply, please see our Personnel Privacy Notice . For more details on how Box Poland protects your information, please see our Supplemental Personnel and Candidate Privacy Notice . NOTICE OF USE OF AI At Box, we believe in the power of AI to improve the recruiting process while keeping people at the heart of every decision. For more information on the use of AI in our hiring process, please visit our webpage here . #LI-hybrid #LI-OB1

Location: Hong Kong 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. We are looking for a Quantitative Data Engineer to join the Data Search & Analytics team. In this role, you will work with the Research and Trading desks to ensure the successful leveraging of data at the firm. Your future role within QRT This team is integral to the firm’s success. As such, your responsibilities will include: Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and discretionary trading decisions. Working within our framework to extract, clean, and aggregate data from a wide range of raw sources and formats ensuring robust data extraction processes Managing end-to-end process of onboarding new datasets Proactively solving data related problems to minimise time to production Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit Your present skillset 3+ years of experience as a Data Engineer (or similar position) working with financial data; experience in a buy-side quantitative finance role is advantageous Rigorous about correctness: able to critically assess code and data quality, regardless of origin Experience using AI-powered development tools to accelerate engineering tasks and improve productivity Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas, Polars and NumPy Familiarity with SQL and relational databases Demonstrable interest in financial markets and the application of data in its analysis and understanding Experience working with both traditional and alternative financial datasets Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors Experience creating documentation and providing direct support to help stakeholders understand and use complex datasets quickly Ability to work in a high-performance, high-velocity environment 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: Warszawa, Poland; Almaty, Kazakhstan; Prague, Czechia; Tallinn, Estonia; Tbilisi, Georgia; Budapest, Hungary; Rīga, Latvia; Vilnius, Lithuania; Lisboa, Portugal; Bucharest, Romania; Madrid, Spain Workplace: fully Customer Description: The customer is a global mobility and urban services platform providing transportation and other on-demand services through a digital marketplace. Project Description: The work spans deep learning model development, large-scale geospatial data pipelines, and low-latency production serving. The candidate will measure the impact through offline evaluation metrics and the results of online experiments Project Phase: ongoing Soft Skills: • Ability to influence teammates and cross-functional stakeholders effectively. • Curious and improvement-oriented mindset with a willingness to challenge existing approaches. • Excellent ability to communicate complex technical findings in a clear and concise manner. Hard Skills / Must Have: • 5+ years of machine learning engineering experience building and deploying deep learning models in production. • Experience building regression, forecasting, or other supervised machine learning systems for production prediction tasks. • Expert-level proficiency in Python and its core data science libraries (e.g., PySpark, Pandas, NumPy, Scikit-learn, PyTorch; gradient-boosting libraries such as CatBoost/XGBoost/LightGBM). • SQL. • Ability to design an ML system from scratch, including data analysis and processing. • Experience translating business goals into ML problems with appropriate metrics and non-functional requirements. • Experience designing and evaluating ML experiments. • Experience with MLOps tools. • Experience working with large-scale geospatial and behavioral datasets. • Experience deploying models to production on ML serving infrastructure and optimizing for latency, and awareness of concept drift and how to detect and manage it. • Comfort working with large-scale geospatial and behavioral data (e.g., GPS traces, H3 spatial indexing) Hard Skills / Nice to Have (Optional): • Academic background in Computer Science, Mathematics, or a related discipline. • Experience with travel time prediction, traffic estimation, or routing quality. • Experience with open-source routing engines. • Knowledge of map matching, speed profiles, road graph tiles, and historical traffic. • Experience with mapping, location, or geospatial products. • Experience building products for developing markets. • Experience with cloud data and machine learning platforms. Responsibilities and Tasks: • Design and build machine learning models to improve routing and travel time prediction. • Develop traffic estimation models using large-scale GPS data. • Implement map-matching solutions for noisy GPS data. • Improve travel time calculation, smoothing, and rerouting logic. • Translate routing objectives into machine learning objectives and evaluation metrics. • Lead offline and online model evaluation activities. • Collaborate with backend engineers to deploy low-latency production models. • Partner with product and operations teams to define new features and requirements. • Own the production ML lifecycle, including serving, monitoring, drift detection, and retraining pipelines. 🧪 Technology Stack: }Python, SQL, PySpark, Pandas, NumPy, Scikit-learn, PyTorch, XGBoost, LightGBM, CatBoost, MLOps, ML Lifecycle Management, Production ML Systems, ML Infrastructure, Geospatial Analytics, GPS Data, H3 Spatial Indexing 📝 Additional notes: The work will be carried out either on client's equipment or via a virtual workstation. Requires fluent Russian , as part of the team communication is conducted in Russian

Location: Serbia Job Title: AI/ML Engineer Department: IT Services /IT Infrastructure Reports To: IT Project Manager Job Overview: The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities: 1. Model Development and Optimization Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. Select appropriate algorithms and techniques based on business needs and data characteristics. Continuously monitor and improve model performance using metrics and feedback loops. 2. Data Preparation and Feature Engineering Clean, preprocess, and transform structured and unstructured datasets for training and inference. Engineer and select relevant features to improve model accuracy and generalizability. Collaborate with data engineers to ensure data quality and accessibility. 3. Model Deployment and MLOps Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. Monitor deployed models for drift, latency, and performance in production environments. 4. AI Solutions and Use Case Implementation Work with business stakeholders to translate real-world problems into AI/ML use cases. Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection). Contribute to proof-of-concept projects and assist in scaling successful models to production. 5. Research and Innovation Stay updated with the latest research, frameworks, and tools in machine learning and AI. Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. Promote innovation by recommending and implementing modern AI strategies. 6. Cross-functional Collaboration Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery. Translate technical insights into business value through clear documentation and presentations. 7. Documentation and Best Practices Maintain comprehensive documentation for models, experiments, and pipelines. Ensure reproducibility, scalability, and compliance with data governance policies. Requirements: Experience: 3–5 years of hands-on experience in machine learning model development and deployment. Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. Technical Skills: Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) Model evaluation, hyperparameter tuning, and pipeline automation REST APIs for model serving and integration Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills, both verbal and written. Ability to work independently and within cross-functional teams. Curiosity, adaptability, and willingness to learn continuously.

Location: Romania Job Title: AI/ML Engineer Department: IT Services Reports To: IT Project Manager Job Overview: The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities: 1. Model Development and Optimization Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. Select appropriate algorithms and techniques based on business needs and data characteristics. Continuously monitor and improve model performance using metrics and feedback loops. 2. Data Preparation and Feature Engineering Clean, preprocess, and transform structured and unstructured datasets for training and inference. Engineer and select relevant features to improve model accuracy and generalizability. Collaborate with data engineers to ensure data quality and accessibility. 3. Model Deployment and MLOps Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. Monitor deployed models for drift, latency, and performance in production environments. 4. AI Solutions and Use Case Implementation Work with business stakeholders to translate real-world problems into AI/ML use cases. Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection). Contribute to proof-of-concept projects and assist in scaling successful models to production. 5. Research and Innovation Stay updated with the latest research, frameworks, and tools in machine learning and AI. Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. Promote innovation by recommending and implementing modern AI strategies. 6. Cross-functional Collaboration Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery. Translate technical insights into business value through clear documentation and presentations. 7. Documentation and Best Practices Maintain comprehensive documentation for models, experiments, and pipelines. Ensure reproducibility, scalability, and compliance with data governance policies. Requirements: Experience: 3–5 years of hands-on experience in machine learning model development and deployment. Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. Technical Skills: Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) Model evaluation, hyperparameter tuning, and pipeline automation REST APIs for model serving and integration Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills, both verbal and written. Ability to work independently and within cross-functional teams. Curiosity, adaptability, and willingness to learn continuously.

Location: India Job Title: AI/ML Engineer Department: IT Services Reports To: IT Project Manager Job Overview: The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities: 1. Model Development and Optimization Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. Select appropriate algorithms and techniques based on business needs and data characteristics. Continuously monitor and improve model performance using metrics and feedback loops. 2. Data Preparation and Feature Engineering Clean, preprocess, and transform structured and unstructured datasets for training and inference. Engineer and select relevant features to improve model accuracy and generalizability. Collaborate with data engineers to ensure data quality and accessibility. 3. Model Deployment and MLOps Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. Monitor deployed models for drift, latency, and performance in production environments. 4. AI Solutions and Use Case Implementation Work with business stakeholders to translate real-world problems into AI/ML use cases. Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection). Contribute to proof-of-concept projects and assist in scaling successful models to production. 5. Research and Innovation Stay updated with the latest research, frameworks, and tools in machine learning and AI. Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. Promote innovation by recommending and implementing modern AI strategies. 6. Cross-functional Collaboration Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery. Translate technical insights into business value through clear documentation and presentations. 7. Documentation and Best Practices Maintain comprehensive documentation for models, experiments, and pipelines. Ensure reproducibility, scalability, and compliance with data governance policies. Requirements: Experience: 3–5 years of hands-on experience in machine learning model development and deployment. Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. Technical Skills: Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) Model evaluation, hyperparameter tuning, and pipeline automation REST APIs for model serving and integration Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills, both verbal and written. Ability to work independently and within cross-functional teams. Curiosity, adaptability, and willingness to learn continuously.

Location: Remote (Ukraine) About us: Gismart is a value-driven mobile app developer with a strong presence in the Health & Wellness, Utilities, and Music app markets. We have recently achieved a significant milestone of over 1 billion downloads worldwide, taking a step toward our mission of cultivating the well-being of people worldwide. With headquarters in London, UK, Gismart is a dynamic global company with a reach extending across Europe and far beyond. Our determined team consists of 250 individuals who bring diversity, creativity, innovation, and relentless drive to the company. Gismart unites professionals from diverse backgrounds in entertainment, music, and tech, allowing us to play to each other’s strengths and succeed as a team. Our mission: Become a stepping stone on our customers’ journeys of self-improvement. Our values: - Deliver what matters - Respect and support others - Initiate and own - Voiceopenly - Execute with quality If you are passionate about mobile app development and want to join a company that’s reshaping the industry, Gismart is the place for you. We provide exciting career opportunities, a supportive workplace culture, and the chance to contribute to a team that is making a tangible impact. For more information on Gismart, visit gismart.com http://gismart.com. About project FitMe is a fitness app created for people who want to stay active without long, repetitive workouts. It offers short, easy-to-follow routines that can be done at home with no equipment. FitMe is perfect for busy people who want to maintain their health, boost energy levels, and feel good every day — without going to the gym or spending hours on exercise. What you will do: - Support and development of marketing analytics for web/mobile products. - Daily interaction with performance marketers: assessing the effectiveness of campaigns, channels and creatives. - Cohort analysis, LTV and unit economics for scaling decisions. - Prioritizing tasks based on business value and potential impact, balancing urgent requests with long-term strategic initiatives. - Building and maintaining dashboards, reports, and key metrics to support data-driven decision-making. - Ensuring data quality, uncovering insights, and providing actionable recommendations to improve marketing performance. Key qualifications: - 1+ years of experience in a similar analytics role. - SQL proficiency for querying and analyzing large datasets. - Solid understanding of statistics, including experiment design, statistical tests, correlation analysis, and segmentation. - Hands-on experience with BI tools such as Tableau or Power BI. - Ability to effectively communicate insights, presenting analysis results in a clear and compelling manner. - Understanding marketing metrics (CPA, CAC, ROAS, LTV). Would be a plus: - Python skills (pandas, data visualization, statistics) for data manipulation and analysis. - Experience with subscription monetization products – understanding key metrics, user retention, churn analysis, and revenue optimization strategies. - Working with advertising offices (Meta, Google, TikTok, ASA). Employee Benefits: - Remote-First Culture: Our team is diverse and extensive, just like our product portfolio. We provide a flexible working schedule and let you work anywhere in the world, either remotely or in one of our corporate hubs. - Сoworking Compensation: We provide 100% compensation for coworking spaces in Ukraine (except Kyiv, where we have a cozy and autonomous hub) and 50% compensation for coworking spaces worldwide to make sure that everyone has a comfortable and inspiring workspace. - Free Office Lunches: We want you to stay fueled and focused, so we provide delicious free lunches for everyone working from our hubs. It’s one less thing for you to worry about during a productive workday. - Public Holidays Policy: Gismart observes public holidays based on the Ukrainian or Polish holiday calendars. Employees working in other locations are entitled to 12 public holidays per year. - 100% Sick Leave Compensation. - Mental and Physical Health: To help you stay happy and healthy, Gismart will partially cover your medical insurance, sports activities, therapy costs. - Personal Equipment Policy: Of course, we’ll provide you with all the equipment you need or cover the maintenance cost for your own tools. - Personal Learning and Development: We love to see you learn and grow, so Gismart will cover 70% of your professional development courses. We’ll also pay for 100% of corporate English courses. - Time-Off Policy: Every employee gets 18 working days of paid vacation and 3 personal days per year, with an extra day added for each year at Gismart. - Corporate Events: We are remote-first, but we love meeting up in person. Whenever possible, we organize corporate events and team-building activities across all Gismart hubs.

Обязанности: • разработка и совершенствование End-to-End ML-пайплайнов • разработка продакшен-пайплайнов обработки данных • работа с огромными объёмами данных Сбера (петабайты) на PySpark, исследование подходов применения их в моделях • писать эффективный и масштабируемый код для тренировки и инференса моделей на PyTorch, проводить эксперименты на GPU-кластере • performance оптимизации кода по обработке больших массивов данных или онлайн сервисов рекомендаций с высокой нагрузкой • менторинг младших членов команды, обмен знаниями и экспертизой. Требования: • математический бэкграунд • хорошее знание Python и ключевых фреймворков для работы с данными (PySpark, PyArrow, Pandas) • опыт написания качественного production кода • опыт написания промышленных пайплайнов обработки данных, содержащих множество шагов, зависимостей и сложную логику • опыт использования Airflow (или другого industry-standard оркестраторов пайплайнов, т.к. Luigi, Dagster и т.д.) • хорошее понимание баз данных SQL / NoSQL • навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимуществом • опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки. Условия: • комфортный современный офис рядом с м. Кутузовская (опционально) • возможность выбрать удобный график – офис/гибрид/удаленка (опционально) • ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования) • корпоративный спортзал и зоны отдыха • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития • программа адаптации и помощь руководителя на старте (для вакансий уровня Junior) • расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа • гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ • подписка Прайм с возможностью совместного использования на трёх близких • вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — разработка клиент-серверных веб-приложений на Python Требования: — опыт от 4 лет — уверенное владение Python 3+ — опыт с Django/Django REST, FastAPI, Flask, NumPy, Pandas — опыт разработки клиент-серверных веб-приложений — уверенное знание SQL, Git, Linux — опыт работы с LLM системами — понимание алгоритмов и структур данных, принципов ООП — будет плюсом: опыт с ML, высшее техническое образование Условия: — локация: удалённо в РФ (строго РФ) — занятость: полная/частичная (30 часов в неделю) — оформление: ИП, ГПХ — зарплата: от 270 000 до 300 000 рублей в месяц, гросс

Задачи: — Решать сложности бизнес-заказчиков и оценивать полученный результат. — Планировать работу команды (Data Scientists, ML-engineers). — Проектировать развитие системы прогнозирования спроса. — Проектировать с руководителями смежных технических команд совместные интеграции. — Программировать и проводить code review. Требования: — Опыт работы в ML и DS проектах от 5 лет. — Опыт решения задач прогнозирования временных рядов. — Управленческий опыт работы. — Умение писать на Python. — Умение работать с данными на PySpark, SQL или Pandas. — Знание и понимание классических ML алгоритмов (линейная регрессия, деревья решений и градиентный бустинг). — Знание Deep Learning фреймворков (Pytorch, Transformers).

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking research scientists with deep expertise in experimental chemistry to join the team. We welcome chemists from across the field, including medicinal, synthetic organic, physical organic, organometallic, inorganic, analytical, physical, and materials chemistry, as well as formulation science. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert in your area of chemistry with hands-on experience designing, and running experiments, from synthesizing, purifying, and characterizing compounds to studying reaction mechanisms and kinetics. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll drive experimental programs end to end and pressure-test AI-designed molecules, AI-proposed synthetic routes, and AI-predicted mechanisms and properties against real chemistry. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Depending on your area of chemistry, you will: Design multi-step synthetic routes for small molecules and oversee their execution end to end, including route selection, reaction optimization, purification strategy, and interpretation of full characterization data (NMR, LC-MS, HPLC) Design and run mechanistic, kinetic, and spectroscopic studies to explain and predict reactivity, selectivity, and molecular properties Prepare and characterize inorganic and organometallic compounds, materials, and formulations, and relate their composition and structure to their properties Coordinate synthesis and biological evaluation with external contract research organizations and academic partners Evaluate AI-designed molecules, AI-proposed synthetic routes, and AI-predicted mechanisms and properties, drive them to experimental readout, and feed results back to research teams Generate experimental and computational data, for example from quantum mechanical calculations, that research teams use to train and evaluate AI models Apply medicinal chemistry principles, including SAR analysis and physicochemical property optimization, to compound design and prioritization Ensure experimental data across programs is high quality and well documented, including procedures, spectra, and failure modes Communicate findings clearly to chemistry, AI research, and life sciences audiences Minimum qualifications PhD in chemistry Demonstrated depth in your area of experimental chemistry (for medicinal chemists, SAR-driven design and optimization of small molecules,), with recent, sustained hands-on laboratory work Comfort navigating ambiguity and defining problems in a rapidly evolving research environment Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications 5+ years of experience in your area of chemistry beyond the PhD For medicinal chemists, a track record of advancing programs from hit identification through lead optimization Experience directing chemistry activities at contract research organizations Computational chemistry, cheminformatics, or coding skills, for example quantum mechanical calculations (DFT) or Python with RDKit or pandas for data analysis and automation Experience using AI or ML tools in chemistry or the life sciences Publications and/or patents demonstrating scientific impact The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the Role: We are seeking an exceptional Applied Scientist to join our Applied Science team. In this role, you will design, develop, and deploy the algorithmic systems that power Garner's products and drive meaningful impact for our members. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund. What you will do: Own the most ambiguous, high-stakes problems on the team end-to-end, and serve as a technical resource others rely on Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for Find novel ways to frame and solve the team's hardest problems, proving out approaches that others build on Set the bar for quality by reviewing others' work with rigor, and build the standards and evaluation tooling the team relies on Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. What we're looking for: 4+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 2+ years of industry experience with a relevant advanced degree, PhDs preferred A bias toward action, quickly translating ideas into working prototypes to test approaches Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them Deep technical range, with fluency across Garner's data and a habit of staying current with advances in the field Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem Strong communication skills and the ability to synthesize complex algorithmic ideas for senior and external stakeholders, and to secure buy-in for cross-team work A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback What you'll get here You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare. Compensation Transparency: The target base comp range for this position is $200,000 – $230,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Applied Scientist III to join our Applied Science team. Garner is hiring Applied Scientists to design and ship the algorithmic systems at the core of our product. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Ship production algorithmic systems end-to-end, from problem framing to launch to iteration Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for Bring new ideas to your work, experimenting with approaches beyond the obvious to get better results Produce rigorous, well-validated work others can rely on, and review your peers' code and analyses Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. What we're looking for: 2+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent advanced degree A bias toward action, quickly translating ideas into working prototypes to test approaches Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them A solid command of the methods your work calls for and the data your models depend on Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem Strong communication skills, with the ability to present your work clearly to senior stakeholders A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback What you'll get here You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. This is a unique opportunity to work on high-impact search problems in healthcare, helping shape how members find better care through algorithmic systems that directly influence healthcare outcomes. Compensation Transparency: The target base comp range for this position is $158,000 – $190,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: Nicosia Job Overview We are looking for a Senior Performance QA Engineer with experience in GameDev to join our World of Warships PC team. This position is open in our Belgrade or Nicosia office . In this role, you’ll focus on performance testing and automation, helping us identify performance bottlenecks and ensure a smooth and stable experience for our players. You’ll work closely with QA and development teams to investigate, analyze, and improve game performance. If you’re enjoy sharing your expertise and learning from others, and want to contribute to the quality of a large-scale PC game, we’d love to hear from you. Reports to Lead Automation QA Engineer What will you do? Develop and maintain automated tests for functional, performance, and stability testing on Python Develop and maintain core functionality of the automation framework Analyze automated test results and investigate failures Performance testing and profiling of game client and backend services Maintain documentation for existing automated tests, frameworks, and tools Collaborate with other teams and provide support based on automated test results Participate in the development and maintenance of CI/CD pipelines and related tools Work with different teams as internal customers, understand their needs, and provide automation solutions Participate in code reviews and contribute to improving automation code quality What are we looking for? 3+ years of experience in Performance Testing or Performance QA 3+ years of experience in Automation QA or a similar position 1+ year of commercial experience in Python-based automated testing, including writing performance test suites using pytest Experience in Performance testing tools and frameworks (k6, load testing, profiling tools) Experience in analyzing and optimizing game performance (PC games) Experience with Elasticsearch for log collection and analysis Experience with CI/CD systems (Jenkins, TeamCity) Knowledge of PC architecture basics and component interaction (CPU, GPU, memory, disk I/O) Understanding of performance metrics: FPS, frame time, CPU/GPU utilization, memory consumption Knowledge of the theory and methods of software testing and performance testing methodologies Upper-Intermediate (B2) or higher English knowledge What additional skills will help you stand out? Experience in game development or game engines (Unreal, Unity) Experience in log parsing and data analysis with pandas and NumPy Experience in Python profiling and optimization (cProfile, line_profiler) Experience with PostgreSQL performance analysis and query optimization Experience in Docker, docker-compose Experience in monitoring tools (Grafana, Prometheus) Experience with Python async/await and multiprocessing Experience in designing and maintaining performance test infrastructure Experience in Linux-based systems Mentoring experience in QA team Work mode This position is open in our Belgrade or Nicosia office During the probation period: onsite work After the probation period: onsite or hybrid (3 days per week in the office) This role is eligible for relocation & immigration support Benefits Benefits and perks are tailored to the local market and culture. Our benefits in Nicosia include: 21 days annual leave (additional days based on years of service: up to 25 days) Additional paid time off (5 Personal Days, Birthday Leave, Marriage Leave, Compassionate Leave) Sick Leave (10 days top-up to statutory allowance per year) Maternity Leave (18 weeks top-up to statutory allowance per case) Career development and education opportunities within the company English Language courses fully covered by the company upon Manager’s approval Private Health Care Mental well-being program (iFeel) Onsite gym and spa Free parking close to the Nicosia offices, based on availability Free drinks-equipped kitchen in every floor building Eurobank benefits (if applicable) Employee discounts (e.g. restaurants, bars, etc.) Personal Gaming Account Onsite canteen with subsidized prices for food and drinks Company events, Social Clubs Seniority Awards Referral program - You can recommend the best talents to the company and receive a reward Please submit your CV in English to ensure smooth processing and review. About Wargaming Wargaming is an award-winning online game developer and publisher headquartered in Nicosia, Cyprus. Operating since 1998, Wargaming has become one of the leaders in the gaming industry with 15 offices worldwide, including studios in Chicago, Prague, Shanghai, Tokyo, and Vilnius. Our diverse and multicultural team works together to deliver a top-class experience to millions of players who enjoy Wargaming's titles across all major gaming platforms. Our flagship products include free-to-play hits World of Tanks, World of Warships and World of Tanks Blitz. Please see Wargaming Candidate Privacy Policy for details on how Wargaming uses your personal data.

Location: Belgrade Job Overview We are looking for a Senior Performance QA Engineer with experience in GameDev to join our World of Warships PC team. This position is open in our Belgrade or Nicosia office . In this role, you’ll focus on performance testing and automation, helping us identify performance bottlenecks and ensure a smooth and stable experience for our players. You’ll work closely with QA and development teams to investigate, analyze, and improve game performance. If you’re enjoy sharing your expertise and learning from others, and want to contribute to the quality of a large-scale PC game, we’d love to hear from you. Reports to Lead Automation QA Engineer What will you do? Develop and maintain automated tests for functional, performance, and stability testing on Python Develop and maintain core functionality of the automation framework Analyze automated test results and investigate failures Performance testing and profiling of game client and backend services Maintain documentation for existing automated tests, frameworks, and tools Collaborate with other teams and provide support based on automated test results Participate in the development and maintenance of CI/CD pipelines and related tools Work with different teams as internal customers, understand their needs, and provide automation solutions Participate in code reviews and contribute to improving automation code quality What are we looking for? 3+ years of experience in Performance Testing or Performance QA 3+ years of experience in Automation QA or a similar position 1+ year of commercial experience in Python-based automated testing, including writing performance test suites using pytest Experience in Performance testing tools and frameworks (k6, load testing, profiling tools) Experience in analyzing and optimizing game performance (PC games) Experience with Elasticsearch for log collection and analysis Experience with CI/CD systems (Jenkins, TeamCity) Knowledge of PC architecture basics and component interaction (CPU, GPU, memory, disk I/O) Understanding of performance metrics: FPS, frame time, CPU/GPU utilization, memory consumption Knowledge of the theory and methods of software testing and performance testing methodologies Upper-Intermediate (B2) or higher English knowledge What additional skills will help you stand out? Experience in game development or game engines (Unreal, Unity) Experience in log parsing and data analysis with pandas and NumPy Experience in Python profiling and optimization (cProfile, line_profiler) Experience with PostgreSQL performance analysis and query optimization Experience in Docker, docker-compose Experience in monitoring tools (Grafana, Prometheus) Experience with Python async/await and multiprocessing Experience in designing and maintaining performance test infrastructure Experience in Linux-based systems Mentoring experience in QA team Work mode This position is open in our Belgrade or Nicosia office During the probation period: onsite work After the probation period: onsite or hybrid (3 days per week in the office) This role is eligible for relocation & immigration support Benefits Benefits and perks are tailored to the local market and culture. Our benefits in Belgrade include: Additional vacation days based on years of service at Wargaming: up to 5 days on top of the statutory minimum Additional paid time off (5 Personal Days, Birthday Leave, Marriage Leave, Compassionate Leave) Sick Leave Compensation, Maternity Leave Benefits Premium Private Health Insurance Career development and education opportunities within the company English clubs and platform for learning languages Mental well-being program (iFeel) Commuting allowance Company events FitPass membership Discounts for employees Personal Gaming Account Coffee, fruits, and snacks in the office On-site canteen with subsidized prices for food and drinks Seniority Awards Referral program - you can recommend the best talents to the Company and receive a reward Please submit your CV in English to ensure smooth processing and review. About Wargaming Wargaming is an award-winning online game developer and publisher headquartered in Nicosia, Cyprus. Operating since 1998, Wargaming has become one of the leaders in the gaming industry with 15 offices worldwide, including studios in Chicago, Prague, Shanghai, Tokyo, and Vilnius. Our diverse and multicultural team works together to deliver a top-class experience to millions of players who enjoy Wargaming's titles across all major gaming platforms. Our flagship products include free-to-play hits World of Tanks, World of Warships and World of Tanks Blitz. Please see Wargaming Candidate Privacy Policy for details on how Wargaming uses your personal data.