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Location: Tel Aviv-Yafo, Tel Aviv District, Israel About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role This is a AI Software Tech Lead, ML role within Aidoc’s AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products. Responsibilities Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging. Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features. Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems Develop and maintain high-quality, scalable, and efficient code. Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems) Requirements BA/BSc/MSc in Computer Science, Engineering or a related field. 7+ years of experience in developing large scale production systems – including architecture design, research, development and testing. Deep understanding of Computer Science fundamentals – object-oriented design, code optimization, and complexity Passion for building generic and robust software architecture Passion for elegant and effective technological solutions, and a love for clean code Strong experience with Python and advantage to deep learning frameworks such as TensorFlow, PyTorch, etc. Strong ability to lead end-to-end development processes Advantage: Experience in developing AI and machine learning solutions, with a focus on computer vision and NLP. Strong communication and collaboration skills, with the ability to work effectively with a cross-functional team Working at Aidoc Our Perks: Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. Amazing and healthy breakfasts and lunches prepared daily by our personal chef! Stocked up kitchen & meal card Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. Amazing culture - collaborative, transparent & fun! Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Location: Москва, удалённая работа или гибрид, RU; Россия О команде Мы — команда DS в Авито Недвижимости, которая развивает направление новостроек. Это одно из крупнейших и прибыльных направлений Авито.Недвижимости: оно помогает сотням тысяч пользователей находить подходящее новое жильё среди миллионов предложений на рынке. Сейчас направление активно развивается, и мы ищем DS-лида, который возглавит команду. В этой роли предстоит определять развитие DS в новостройках, вместе с продуктом и аналитиками формировать приоритеты и отвечать за результат направления в бизнес-метриках. Какие задачи вас ждут: — возглавлять DS-команду новостроек: управлять беклогом, вместе с продуктом и аналитиками формировать квартальные цели, защищать приоритеты и отвечать за трекшн направления в бизнес-метриках; — формировать долгосрочный план развития DS в новостройках на год и более и определять ключевые направления работы команды; — развивать сотрудников команды: определять зоны ответственности, формировать планы роста и проводить performance review; — держать целостную техническую картину системы: принимать архитектурные решения, проводить дизайн-ревью моделей, отвечать за корректность экспериментов и воспроизводимость результатов; — отвечать за надёжность и стоимость владения ML-сервисами: контролировать SLA продовых сервисов, регулярное переобучение моделей и мониторинг drift, а также планомерно работать с техническим долгом ML-платформы. Мы ждём, что вы: — имеете 4+ лет опыта в Data Science; — имеете опыт управления DS-командой; — умеете говорить с бизнесом и аналитиками на языке метрик и денег, защищать приоритеты и аргументированно говорить «нет»; — отлично знаете классические алгоритмы и понимаете границы их применимости; — имеете практический опыт работы в NLP. Будет здорово, если вы: — имеете опыт работы с LLM. Работа у нас — это: — возможность влиять на продукт: ваши решения будут улучшать опыт миллионов пользователей; — сложные технологические задачи на большом масштабе; — мощное железо: доступ к производительным GPU-кластерам для экспериментов; — сильное комьюнити: команда экспертов, с которой можно обсуждать идеи и подходы; — развитие: бюджет на обучение, курсы, конференции и профессиональную литературу; — расширенная забота о здоровье: ДМС, страхование жизни, онкострахование; — сервис психологической поддержки, а также финансовые, юридические и ЗОЖ-консультации для вас и ваших близких; — корпоративный спорт: групповые тренировки, велбиинг-приложение; — спецпредложения от партнёров и скидки на сервисы Авито: бронирование жилья, услуги продвижения, ипотечное страхование; — компенсация питания.

Location: Hybrid - Palo Alto or San Francisco 📍 Hybrid, Palo Alto or San Francisco (Hybrid – 2 days/week in office) Reports to: Director Data Science + Analytics Job Type: Full-time W2 About the Role We are looking for a highly analytical and business-minded Senior Data Analyst to design, build, and own the end-to-end analytical framework for our most critical operational asset: our clinician workforce. In this role, you will own the data ecosystem spanning the entire clinician lifecycle—from the moment a provider enters our recruiting funnel, through onboarding, credentialing, and state licensing, to their ongoing clinical performance, operational efficiency, and downstream business impact on patient retention. You will develop performance frameworks that merge operational SLAs (e.g., on-time arrival, inbox turnaround times) with clinical quality and safety metrics. Additionally, you will lead our efforts in provider interaction analytics, creating evaluation and scoring logic to quantify qualitative behavioral dimensions, such as clinician empathy from consultation transcripts. Sitting at the intersection of Clinical Operations, Quality, Talent, Business Strategy, and Product, you will serve as the primary analytical partner to our Clinical Leadership and Executive team. What You’ll Do 1. Clinician Lifecycle & Funnel Analytics Recruiting & Onboarding Optimization: Track and analyze the provider hiring funnel to uncover drop-off points, streamline time-to-hire, and improve conversion rates across clinical specialties. Credentialing & Licensing Efficiency: Build predictive frameworks and monitoring dashboards to reduce state-by-state licensing bottlenecks and decrease provider time-to-first-consultation. Cohort Retention & Attrition Modeling: Analyze first-year clinician retention trends, identifying early-warning indicators of burnout or regrettable turnover, and evaluating the long-term impact on operational capacity. 2. Operational Performance & Efficiency Metrics Operational SLA Tracking: Design and maintain performance scorecards tracking operational efficiency metrics, including appointment on-time start rates, EMR/EHR inbox turnaround times, chart completion speed, and panel utilization. 3. Clinical Quality, Safety & Interaction Scoring Transcript & Empathy Analytics: Establish scoring frameworks and evaluation logic to extract insights from visit transcripts. Quantify qualitative provider attributes (e.g., patient rapport, empathy, active listening) using sentiment and text analytics LLM tools. Clinical Safety & Quality Alignment: Partner with the Clinical Quality and Safety teams to incorporate chart audit scores and clinical safety compliance into unified provider scorecards. 4. Downstream Patient & Business Impact Clinician Impact on Patient Retention: Conduct causal and correlation analyses linking specific clinician behaviors, operational SLAs, and empathy scores directly to patient retention, net promoter scores (NPS), and long-term treatment plan adherence. Executive Reporting & Strategic Guidance: Translate complex provider performance data into clear executive dashboards and strategic frameworks that directly inform clinician compensation, training programs, and operational workflows. What You Bring Technical Skills Advanced SQL & Data Modeling: Expert-level SQL skills for querying, transforming, and modeling complex relational databases across disparate operational and EHR systems. Python Proficiency: Advanced skills in Python for statistical analysis, cohort modeling, survival analysis, and text/sentiment processing. Data Visualization & BI: Proven ability to design intuitive, executive-ready dashboards in modern BI tools (e.g., Looker, Tableau, PowerBI). Text Analytics & NLP Awareness: Familiarity with text mining, sentiment analysis, or prompt-based LLM evaluation frameworks for processing qualitative data (transcripts, chat logs, survey notes). Modern Analytics Stack & AI Tools: Experience with cloud data warehouses (Snowflake, BigQuery, Databricks) and active adoption of modern AI tools (e.g., LLMs for coding efficiency, automated insights) to accelerate analytics workflows. Analytical & Domain Capabilities Healthcare Operations Intuition: Understanding of clinical operations, provider scheduling, EMR/EHR workflows (e.g., Epic, Athena, or proprietary telehealth EHRs), and clinical quality metrics. Behavioral & Lifecycle Analytics: Experience with cohort analysis, retention modeling, and constructing behavioral/qualitative scoring models. Strategic Problem Structuring: Ability to take unstructured business and clinical questions and translate them into rigorous, answerable quantitative frameworks. Cross-Functional Influence: Demonstrated ability to partner effectively with non-technical stakeholders, particularly Clinical Lead/Medical Directors, Operations leads, and Talent teams. Experience 5+ years of data analytics experience delivering high-impact operational or workforce insights. Healthcare Experience: Strong preference for background in Digital Health, Telehealth, Tech-enabled Medical Groups, or Health Operations. (Strong candidates with backgrounds in People Analytics/People Data Science with exposure to operational telemetry are also encouraged to apply.) Bachelor’s or Master’s degree in Quantitative discipline (Data Analytics, Health Informatics, Statistics, Industrial Engineering, Economics) or equivalent practical experience. Interview Process: Recruiter Screen- 30 mins Hiring Manager Screen- 30 mins Technical Screen- 1hr Panel Interviews- 3 hours + Lunch in Office in Palo Alto At this time, Midi is unable to provide visa sponsorship . Candidates must be authorized to work in the U.S. without current or future sponsorship needs. This is a full-time W2 position. The base salary range is 150-175K and will depend on experience. Midi pays a competitive base salary, plus equity and benefits. While you’re waiting for us to review your portfolio, here’s some fun content to check out 🎥 https://www.youtube.com/watch?v=1px7i6MVjNg #LI-PS1 At this time, Midi is unable to provide visa sponsorship. All Candidates must be authorized to work in the United States without current or future sponsorship needs. Please note that all official communication from Midi Health will come from an @joinmidi.com email address. We will never ask for payment of any kind during the application or hiring process. If you receive any suspicious communication claiming to be from Midi Health, please report it immediately by emailing us at careers@joinmidi.com . Midi Health is an Equal Opportunity Employer. We are committed to pay equity and ensure that all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Our compensation philosophy is based on fair, objective criteria and the impact of the role, regardless of an applicant’s salary history. Please find our CCPA Privacy Notice for California Candidates here .

Location: Limassol, Cyprus; Tbilisi, Georgia Workplace: hybrid TradingView is the world’s largest financial analysis platform with more than 100M users across 180+ countries. We build tools that help traders and investors make informed decisions — from advanced charting and market data to collaboration and publishing features. Our products are used daily by millions of individuals and trusted by companies like Revolut, Binance, and CME Group. We’re continuing to grow and scale our platform, and we’re looking for people who care about product quality, take ownership of their work, and want to build systems used by a global audience. About the team We develop and implement machine learning and AI solutions across a range of products: AI assistants, customer support chatbots, intelligent data processing, generative AI features, recommender systems, spam detection, search and other ML-powered modules. Our goal is to build reliable ML and AI systems that solve real product problems — from experimentation and prototyping to production integration and continuous improvement. Responsibilities Designing and implementing ML and AI modules for various products, from experimentation and prototyping to production integration Building solutions based on LLMs and other ML/NLP approaches for data processing, generation, search, assistants, bots, agents and automation Choosing and evaluating appropriate approaches — including external AI providers, open-source or self-hosted models, as well as traditional ML/NLP methods Contributing to the architecture of ML solutions, shaping technical approaches and engineering standards Preparing and processing data, training models, running A/B tests, and analyzing results Monitoring and improving model performance, interpreting model behavior and key metrics Evaluating AI-system quality, analyzing failure cases and improving models, prompts, data and system architecture Collaborating with product managers, engineers, and analysts to clarify requirements, integrate solutions, and evaluate their impact Working with MLOps infrastructure: CI/CD, monitoring, logging, containerization What makes you the perfect fit 3+ years of experience in ML engineering and building production-ready ML systems Strong practical expertise in NLP, LLMs, AI assistants and related AI/ML areas Experience with both modern LLM-based systems and traditional ML/NLP approaches such as classification, ranking, retrieval, semantic similarity and information extraction Strong track record of delivering end-to-end ML solutions — from idea and data to production and support Proficient Python skills and experience with production-grade development Experience evaluating ML/AI solutions and understanding their quality, reliability, latency and cost trade-offs Solid knowledge of A/B testing and result interpretation Experience in architectural decision-making and a drive to improve engineering practices Familiarity with tools like Docker, Kubernetes, CI/CD systems, monitoring (e.g. Prometheus, Grafana), and logging Will be a plus Product-oriented mindset and understanding of business metrics Experience building real-time and high-load ML systems Experience with open-source or self-hosted models Familiarity with modern MLOps tools (e.g. MLflow, Airflow, Kubeflow) Experience evaluating the UX of AI-driven interactions What we offer you Flexible working hours and a hybrid work format Well-equipped offices for focused and collaborative work A global, distributed team of 500+ professionals Learning, mentorship, and long-term career growth Relocation support and private health insurance Performance-based bonuses TradingView Premium access Regular team events and company-wide meetups Join the TradingView team and help us build a product used by millions of traders and investors worldwide. We look forward to hearing from you! TradingView is an equal opportunity employer. We embrace diversity and are dedicated to fostering a diverse and inclusive workplace. Our success is driven by 600+ professionals from 40+ countries who speak nearly 20 languages.

Location: Москва, офис или гибрид, RU; Россия О команде AI Speech Lab — внутренний ML-продукт Авито. Команда анализирует пользовательские диалоги, чтобы повышать эффективность продаж и находить возможности для развития продуктов Авито. Мы создаём платформу Business Insights, которая извлекает «голос пользователя» из диалогов и оцифровывает его. Платформа помогает быстрее понимать реальные потребности пользователей: объединяет качественную обратную связь — контекст и цитаты из диалогов — с количественной оценкой её массовости. Это сокращает время получения инсайта для продуктовых исследований с нескольких недель до 15 минут. Какие задачи вас ждут: развивать продукт, который помогает пользователям самостоятельно находить ответы и проводить исследования по неструктурированным данным без привлечения ML-команды или аналитиков; укреплять доверие к данным платформы среди лидеров вертикалей и продуктовых команд: делать инструмент частью процессов принятия решений, повышать прозрачность и доказуемость инсайтов, например через быстрый переход к цитате из диалога; развивать продукт за пределами звонков B2B-продаж: интегрировать текстовые чаты, обращения покупателей в поддержку и отзывы, чтобы сформировать единую картину по всем каналам; находить баланс между стоимостью LLM-оценки, репрезентативностью выборки и скоростью, чтобы сократить время ожидания инсайта с нескольких часов до 15 минут. Мы ждём, что вы: имеете от 3 лет опыта в DS/ML или продуктах на основе данных и практический опыт с LLM-приложениями; умеете работать с количественной и качественной обратной связью: систематизировать разрозненные данные, находить корневые проблемы пользователей и переводить их в язык оцифрованных метрик; умеете работать с данными: читать и проверять витрины в SQL, корректно ставить задачи DS/DE и принимать результаты; создавали инструменты самостоятельной аналитики или платформы внутренних данных; работали с неструктурированными данными: NLP, текстами, аудио, системами речевой аналитики или VoC; понимаете специфику B2B-домена, процессов продаж или клиентского сервиса. Работа у нас — это: влияние на бизнес, работа с LLM/ML, культура обмена опытом, прозрачный карьерный трек, развитие в сильной экспертной среде; расширенная забота о здоровье: ДМС, страхование жизни, онкострахование; сервис психологической поддержки, а также финансовые, юридические и ЗОЖ-консультации для вас и ваших близких; корпоративный спорт: групповые тренировки, велбиинг-приложение; спецпредложения от партнёров и скидки на сервисы Авито: бронирование жилья, услуги продвижения, ипотечное страхование; компенсация питания.

Location: Hong Kong, Singapore, Shanghai, Beijing Programme duration: 3–6 months, starting in 2027 Who qualifies: Penultimate or final-year students completing a bachelor’s, master’s or PhD degree Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes and markets worldwide. Our approach to investing is scientific: we bring together data, research, technology and trading expertise to develop and run systematic strategies. Research is central to how QRT invests. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from high to low frequency. This gives our researchers access to large and diverse datasets, sophisticated research tools and the infrastructure needed to turn research ideas into live trading strategies. Our internships are designed to give students meaningful experience of that process. You’ll join a systematic team, work on real research or trading problems and learn from experienced researchers and traders. The environment is rigorous and collaborative: ideas are tested against data, assumptions are challenged and good questions matter as much as quick answers. Your future role at QRT Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on, with the aim of finding the strongest fit. As a Quantitative Research Intern, you could contribute in one of two complementary areas within one of QRT’s systematic teams, spanning high, mid and low frequencies: Research Your focus will be on developing predictive signals from large and varied datasets. You’ll explore the data for patterns and form hypotheses about what might be driving them. From there, research is iterative: you’ll design tests, question the results, adjust your approach and test again. Working with other researchers, you’ll learn to distinguish promising signals from noise. In doing so, you’ll experience the full research process, from an initial observation to something that can be used in live trading. Trading You’ll contribute to the live deployment of QRT’s research by working directly with our systematic trading platform. You’ll monitor how signals behave in production, track performance, improve execution efficiency and help identify and manage potential risks. Working closely with senior Researchers and Traders you’ll investigate how strategies behave in production and look for ways to make them more robust and scalable. You’ll use quantitative analysis and programming to understand what is happening in live systems and determine where improvements can be made. Across both areas, how you approach a problem matter. We’re looking for interns who are curious, creative and collaborative. You should be comfortable exploring ideas, asking questions and learning as you go. Your present skillset Academic background – Pursuing an advanced degree in a quantitative field such as Data Science, Statistics, Mathematics, Physics or Engineering. Quantitative foundations – Strong analytical skills and an interest in using mathematics, statistics and computation to understand complex problems. Programming – Coding experience in at least one leading programming language, including Python, C++ or C#. Research interests – Knowledge of statistics, machine learning, NLP or AI techniques is useful but not essential. Data – Experience exploring large datasets across multiple time horizons is a plus. Problem solving – Able to work through complex problems rigorously while maintaining strong attention to detail. Independence and collaboration – Comfortable working autonomously while exchanging ideas and working closely with colleagues from different disciplines and backgrounds. Communication – Able to explain your reasoning and communicate technical ideas clearly. Languages – Fluent in English; additional languages are a plus. Interviewing Apply Online – Submit your application online. Applications are reviewed on a rolling basis by our Talent Acquisition team. We read applications carefully, so thoughtful answers that explain your interests and motivations are useful. Technical Assessment – Selected candi dat es will complete a coding challenge focused on core programming and problem-solving skills . Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your quantitative and technical thinking, how you approach unfamiliar problems and how you work with others. We also encourage candidates to take part in one of our Data Challenges . These are an opportunity to work on problems relevant to quantitative research and demonstrate your analytical and technical approach. Strong performance may lead to direct follow-up from our team: Challenge dat a (ens.fr) 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: 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: Limassol, Cyprus Workplace: on-site Mayflower is a technology company that alters the entertainment industry to a new level of perception and engagement. We are building the future of live entertainment. We believe that by providing people with the best and highest-quality live streaming experience in entertainment, we can tackle the world’s “problems” better, together! We are seeking an experienced Python Developer (ML) to join our dynamic team ML team. Our technology stack: Languages: Python; Monitoring: Prometheus, VictoriaMetrics, Grafana, Grafana Loki, Sentry; DBs: MariaDB, Clickhouse, Redis; Streaming: Apache Kafka; Workflow management: Apache Airflow, Argo Workflow; Infrastructure: k8s, gitlab. Job Responsibilities Design and build production-grade Python services for running and maintaining ML applications for different domains: RecSys, CV, Classic ML, NLP. Develop and maintain data pipelines for training, validation, batch inference workflows Build internal tools and reusable modules for the ML team Implement monitoring and observability for ML services using metrics, logs, and dashboards. Contribute to continuous integration and delivery pipelines (testing, packaging, and automation). Develop visualization and debugging tools for model outputs — including active learning and content analysis interfaces. Ensure that all components are reliable, testable, and easy to maintain. You’ll thrive here if you have 3+ years of experience as a Python Developer, Backend Engineer, or Data Engineer. Strong Python skills (asyncio, FastAPI, pydantic, typing, modular architecture). Proven experience designing and deploying production systems with Docker, Kubernetes and CI/CD. Familiarity with ML workflows (you don’t need to train models yourself, but you understand how they’re served, retrained, and monitored). Experience building data pipelines and integrating with various data sources. Knowledge of metrics, logging, and observability best practices (Grafana, Prometheus, Loki, etc.). Strong understanding of testing, clean code, and maintainable software design. Qualification that can be a plus: Experience working with machine learning teams or MLOps pipelines. Experience with distributed systems or high-load backend services. Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR Interview (40 min); Technical Interview + Live Coding (1.5 hour); Final Interview (1 hour).

About Us & The Team Til-Qazyna is a national scientific and practical center dedicated to building the core digital and AI infrastructure for the Kazakh language. We develop foundational language resources, linguistic tools, and open-source models, including custom text corpora, morphological analyzers, RAG pipelines, and fine-tuned Large Language Models. We are looking for an AI Engineer to focus exclusively on natural language processing, corpus engineering, and LLM fine-tuning. Key Responsibilities • LLM Adaptation & Fine-Tuning: Fine-tune, evaluate, and benchmark open-source LLMs (Llama, Mistral, Qwen, Gemma) for Kazakh language understanding and generation using parameter-efficient methods (LoRA, QLoRA, PEFT). • NLP & Linguistic Tooling: Develop, maintain, and optimize rule-based and neural NLP components, including morphological analyzers, lemmatizers, tokenizers, and terminology parsers. • Corpus & Data Pipelines: Design automated pipelines for large-scale text crawling, data cleaning, deduplication, synthetic data generation, and dataset curation. • Inference & Deployment: Package NLP models and LLMs into containerized microservices (Docker, FastAPI) and optimize inference using modern serving frameworks (vLLM, Ollama, TensorRT-LLM, ONNX). Requirements • 1+ years of hands-on experience as NLP / AI / Machine Learning engineer. • Solid understanding of the Transformer architecture, attention mechanisms, embeddings, and tokenization. • Experience with core ML/NLP libraries: PyTorch, Hugging Face (transformers, datasets, accelerate, peft), Scikit-learn. • Experience building data preprocessing pipelines and working with structured/unstructured text data. • Practical knowledge of Docker, Linux, and Git. • Degree in Computer Science, Data Science, Applied Mathematics. Nice to Have • Hands-on experience with modern LLM serving and optimization engines (vLLM, TGI, llama.cpp, quantization techniques like AWQ/GPTQ). • Experience with RAG stacks (LangChain, LlamaIndex, ChromaDB, Qdrant, FAISS). • Understanding of the morphological, agglutinative, or grammatical characteristics of the Kazakh language. • Familiarity with alignment techniques (DPO, RLHF) or synthetic data generation. What We Offer • Direct impact on sovereign AI development and language technology used at scale. • Official employment in full compliance with the Labor Code of the Republic of Kazakhstan. • Access to high-performance GPU compute clusters for model training and experimentation.

Location: Cairo, Egypt Workplace: remote As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com   To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.     Main Purpose of the Role   We are looking for translators with experience in English into Arabic(All Countries) Patent Translators/LQA reviewers (native-level fluency of languages specified)  with immediate availability for a patent translation project in the fields of Mechanics, Computer Science and Chemistry.   Project Details:   Job Title: English into Arabic(All Countries) Translator/LQA Reviewer Start Date: ASAP Location: Remote Content Specialties: "Chemistry","Computer Science","Electricity"  Task Type: Translation; LQA Review CAT Tool: XTM/JIRA  Employment Type: Freelance Main Duties Translate and review patent-related content from English into Arabic(All Countries) , with original meaning conveyed in a manner that is readable and understandable to target audience. The Style adequacy is a key aspect for our client; Follow instructions, for example Translation process, CAT tool usage, etc. Communicate effectively and response promptly in English. REQUIRED SKILLS Native fluency in Arabic Degree in linguistics, translation or equivalent experience Minimum 2 years’ experience in the translation and/or editing of patent documents. Proficiency use of CAT tools, especially with XTM, JIRA Attention to detail Good availability and quick response times Selected candidates will be invited to complete an the translation test. Approved linguists will be then included in our pool of external partners and professional details will be made available to our global Production teams.   We look forward to hearing from you!   Welocalize Talent Management Team

Location: Houston; Austin; Dallas; San Antonio Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Role Overview: In this role, you will have ownership of the full sales cycle - from identifying leads to closing deals with Global 2000, large enterprises within the Energy (oil and gas) and Utility sectors. We’re looking for an approachable and compelling communicator who loves working with prospects to uncover their needs and feels comfortable developing tailored value propositions around how Cohere’s platform can help them achieve their business goals. You’ll lay the foundation for Cohere’s growth by owning your territory and collaborating with teammates across customer success, sales development, marketing, and solution architecture. You’ll be the voice of the field and help our product and engineering teams prioritize the Cohere roadmap with customer-centric care. It’s a highly self-directed role, so you should be someone who thrives in an unstructured and quickly evolving environment. And your opportunity for impact will be astronomical — Cohere has skies-the-limit potential, and you’ll help us reach it. Key Responsibilities: As a Strategic Account Executive focused on the Energy & Utilities industry, you will: - Focus on net-new logo acquisition via outbound activity and relationship building with key stakeholders while also bringing a strong network of key decision-maker and influencer contacts and relationships in the energy (oil and gas) and utility industries to accelerate engagements, drive strategic partnerships and win sales opportunities - Work closely with customers and prospects as a consultative, trusted advisor who deeply understands their challenges and goals, their technology ecosystem, and will tailor solutions to drive measurable impact for their businesses - Work in close partnership with channel partners to find opportunities to scale outreach and customer satisfaction in your region - Collaborate with product and engineering teams as well as customer success on strategic motions to deliver solutions to large enterprise customers - Collaborate with Sales Development Representatives to drive top of funnel activity - Own the full sales cycle – from initial outreach through proof-of-concept, pilot, deal close, and deployment ; this is not a transactional sale that you can walk away from after the contract is signed but rather requires ongoing oversight of the project to ensure success Key Responsibilities: You may be a good fit if you have: - 8+ years of previous B2B sales experience with Global 2000, large enterprises in the energy (oil and gas) and utility sectors, negotiating and closing transformational multi-year (2-5 year) SaaS deals in the 7 figure range, and a track record of high performance and exceeding quota - Previous experience as a technical consultative salesperson, selling complex products, such as developer tools, API products, or AI / NLP solutions, are a plus, with a focus on applications in the energy (oil and gas) and utility sector - Previous experience working with customers during the deployment phase of the engagement, aligning on how best to configure and customize the solution that supports success in production and builds trust to set up for expansion and growth - Previous experience working with channel partners such as cloud hyperscalers and system integrators to drive sales cycles and hit shared revenue goals - High tolerance for ambiguity - as an early sales hire, you’ll have to be a self-starter, doer and a strategist who is capable of wearing many hats and doing what it takes to figure out a path to success - Curiosity - you want to go deep on NLP and become an expert on our technology while considering how to fit into a large organization’s technology landscape with a focus on its applications in the energy (oil and gas) and utility sectors - Fantastic communication skills - you are a great listener, have a knack for understanding what matters most to others, build strong relationships, can speak to the c-suite, and feel comfortable speaking to both technical and non-technical audiences in the energy (oil and gas) and utility sectors Qualifications: - Deep understanding of the energy (oil and gas) and utility industries, including key trends, challenges, and opportunities - Ability to articulate the value of AI and NLP solutions in the context of energy (oil and gas) and utility operations, such as predictive maintenance, supply chain optimization, and customer engagement - Experience working with regulatory and compliance requirements specific to the energy (oil and gas) and utility industries Cohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-related knowledge, skills, education, and experience. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. A degree in Computer Science  or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.

Задачи: - Разработка и обучение ML/DL-моделей для задач NLP и Computer Vision, возможен также classic ML. - Анализ и обработка данных. - Работа с PyTorch. - Тестирование и оптимизация моделей. - Подготовка модели к запуску в продакшене, участие в A/B тестах, поэтапных раскатках и мониторинге качества. - Поддержка существующих моделей. Требования: - Широкий прикладной ML-бэкграунд: опыт работы минимум с двумя направлениями из Computer Vision, NLP / LLM, classic ML (обучение моделей, интеграция их в реальные проекты). - Коммерческий опыт в Data Science / ML от 4 лет. - Уверенное знание Python и PyTorch. - Хорошее знание классического ML и современного DL (включая математику за ними). - Опыт самостоятельного ведения задач на разных этапах проекта. - Умение переводить бизнес-задачу в ML-постановку и предлагать практичные решения.

Задачи: - Разработка и обучение ML/DL-моделей для задач NLP и Computer Vision, возможен также classic ML. - Анализ и обработка данных. - Работа с PyTorch. - Тестирование и оптимизация моделей. - Подготовка модели к запуску в продакшене, участие в A/B тестах, поэтапных раскатках и мониторинге качества. - Поддержка существующих моделей. Требования: - Широкий прикладной ML-бэкграунд: опыт работы минимум с двумя направлениями из Computer Vision, NLP / LLM, classic ML (обучение моделей, интеграция их в реальные проекты). - Коммерческий опыт в Data Science / ML от 4 лет. - Уверенное знание Python и PyTorch. - Хорошее знание классического ML и современного DL (включая математику за ними). - Опыт самостоятельного ведения задач на разных этапах проекта. - Умение переводить бизнес-задачу в ML-постановку и предлагать практичные решения

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Engineer, you'll be the technical anchor for GitLab's Nonlinear Productivity team in the US: the person who decides what "proven" means before something ships, and who helps shape what the team builds next, not just how to build it. It's a from-scratch, generalist team with no dedicated product manager — that ownership starts on day one. Some examples of the problems this team takes on: Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions. Turning a manual, error-prone release step into an agentic workflow that catches its own mistakes before a human ever has to. What you'll do Set the technical direction for the team's agentic systems, from how agents are orchestrated to where a step should stay human-owned, and defend those calls once they're tested against real code. Discover and prioritize sources of friction across GitLab's SDLC, driving the fix — agentic, process-based, or both — from a rough hypothesis through to a shipped, measured result. Work across any part of GitLab's codebase as the problem requires, since this team operates like a small, generalist group rather than one scoped to a single service. Apply distributed systems judgment to catch cases where generated code looks correct but breaks under concurrency, at scale, or across deployment topologies (including self-managed, dedicated, and multi-tenant environments), and coach others to do the same. Mentor senior and mid-level engineers on agent engineering practices and distributed systems judgment, through design reviews and pairing that raise the team's collective bar rather than just your own output. Collaborate with the India-based group a few times a week to align on the roadmap, and represent the team's technical progress to stakeholders in the Chief Technology Officer's organization. Serve as a bar raiser for the team's hiring, owning the Technical Leadership round for other Staff-level candidates as the team scales. Own a greenfield technical foundation from day one, with your scope and impact free to grow as the team scales. Take part in on-call or operational support where your team’s ownership model requires it. What you'll bring Experience building reliable agentic or large language model (LLM)-based systems, including multi-step orchestration, tool use, guardrails, and recovery. Ability to work autonomously in unfamiliar codebases and drive solutions from discovery through completion. Strong distributed systems and computer science fundamentals, including coordination, consistency, idempotency, rate limiting, failure modes, and degradation under load. Proficiency in Go, Rust, or Python, with the ability to read and modify code in the others. A track record of delivering results from unclear or incomplete requirements — able to take a complex, loosely specified problem and decompose it into a concrete proposal of small, shippable steps. Experience designing evaluation frameworks for systems where "looks plausible" and "is actually correct" are different questions, and a track record of raising the quality bar for a team's output, not just your own. A history of unblocking and enabling teammates — through design reviews, technical writing, or mentoring — and of engaging regularly with other teams to find where collaboration actually pays off. About the team Nonlinear Productivity — shortened internally to "NLP," with no relation to natural language processing — is one of GitLab's newest teams: a strategic incubation group that reports into AI Platform leadership under the direct sponsorship of the CTO. It's split into a US group (this role) and an India-based group working the same charter; the two sync on roadmap and tooling a few times a week but otherwise run day to day on their own. Solutions that prove out internally are the team's path to a monetized, customer-facing GitLab offering. It's a good fit for engineers who want technical ownership of something with no existing playbook, and a hand in defining a brand-new part of GitLab from its first commit. Remote-Global The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800 — $259,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: New York, NY or Remote About Us: EvolutionIQ’s mission is to deliver state of the art technology that helps insurance claims teams make claims handling more accurate, fair, and efficient, so that more people impacted by injury or illness can continue their lives with dignity and stability. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row and Built In’s Best Places to work in 2025 and 2026! About You : A Senior Machine Learning Engineer who thrives on first principles problems that no one has ever worked on before. You love innovation and making an immediate impact, and are constantly driving toward launch and delivery thanks to your high degree of ownership and control. You love working on new and challenging problems, not incremental or marginal improvements, and you're supercharged by having interesting, unsolved problems continually present themselves. In this Role, You Will: Build ML models for production use Perform in-depth exploratory data analysis to scope ML opportunities, identify potential issues in the data, and lay the groundwork for model design, training & evaluation strategies Suggest and implement new features to improve model performance and business logic Write and review production-quality PRs daily Translate client business problems into ML problems Build scalable machine learning models for claim time series forecasting and NLP text understanding Continue to grow and learn in the data & ML space with a focus on business problems that require making sense of large-scale structured and unstructured datasets Requirements : 2+ years of experience as a Machine Learning Engineer or Data Scientist, preferably in highly scalable production environments. You have deep exposure to data science & ML tech stacks (sklearn, Keras / PyTorch, tuning frameworks), data analysis & modeling, feel at home in Python/Pandas/Jupyter, and strive for scalable technical concepts and solutions. You have excellent written and verbal communication skills and can effectively correspond between technical and non-technical audiences. You’re a team player who is solutions-oriented. Experience leveraging Claude Code and related tools is a strong plus Even Better if You Have the following: Knowledge of Dagster, BigQuery, Vertex AI, GCP, Terraform, Spark, Kubernetes Owned and deployed, and maintained model-serving pipelines in production Expert skills at writing clean, efficient, and easy-to-understand code with unit tests and functional design patterns Experience with advanced statistical modeling, especially probabilistic programming Ambitious, collaborative, and empathetic values A work style that is open to giving and receiving critical feedback and collaborating effectively across teams Work-life, Culture & Perks: Compensation: The base salary range is $190-225K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package. Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits. Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work. Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend. Growth & Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement. Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer. EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.