Вакансии

Location: Limassol Cyprus Workplace: OnSite About Scorewarrior. We're a game developer and publisher from Cyprus with one single game in the 4x strategy genre: Total Battle. We're a one-game company on purpose, because in everything we do, we focus We are currently concentrating on two major goals: - To make our game #1 in its genre. - To make our company the best place to work on games. And we're far from there; we still have a lot of work to do. That's why we need you.   Let's dive in. As our marketing Senior Data Scientist you will play a key role in optimizing our marketing strategies by providing meaningful insights through advanced modeling. Your primary focus will be to build predictive models that forecast user payment behavior by Day30, based on in-game activity data collected during the first 7 days of a user’s lifetime.   Key responsibilities. - Build and refine predictive models to forecast users payment likelihood. - Explore and process large volumes of in-game event data to uncover patterns relevant for forecasting. - Collaborate with the marketing team to ensure that the models drive better user acquisition decisions. - Effectively manage large datasets, ensuring timely and precise insights.   You could be a great fit for this position If: - You have at least 4 years of experience in data science. - You have a proven track record in creating and implementing predictive models related to customer behavior. - You possess strong Python skills and experience with key machine learning libraries (scikit-learn, pandas, numpy, XGBoost, LightGBM, TensorFlow, PyTorch). - You have experience working with large datasets and are capable of effectively diving deep into detailed analyses. - You excel at translating complex analytical concepts into clear insights and recommendations for stakeholders across all levels. - You love game development. - Your English is B1 and higher, you Russian is B2 and higher.   Why Scorewarrior? - Work with a product you love: Total Battle is more than just a job; it's a passion project. - Join a highly skilled team: We're a nerdy group of talented individuals who love what we do. - Make a real impact: Your work pulls the best people together to get us to that number-one app store spot. - Stability: Start working with a stable three-year contract with the potential to extend it to infinity and beyond. - An excellent remuneration package, including a 13th salary. - Full-coverage relocation for you and your family to Cyprus (Limassol). - Private health insurance for you and your family members. - A monthly pre-school, school, and university allowance for employees' children. - Lunch compensation. - A sports and fitness allowance. - Personal development opportunities paid for by the company: professional and language courses, books, etc. - Bonuses for outstanding results, years worked, getting married, and the birth of a child. - Monthly office parties and epic, annual offsite company birthday and Christmas parties.     Do you accept the challenge? Apply today!

Location: Metro Manila; Armenia; Kazakhstan; Georgia Workplace: Hybrid Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia, starting in the Philippines. We combine global fintech expertise with deep local market knowledge to make financial services simple, accessible, and useful for millions of people across the region. 7M+ app downloads. 2M+ monthly active users. 7,000+ partner stores. US$310M+ raised from leading global investors. Manila-based, globally distributed, and hybrid-first — our team spans 45+ countries. If you want to solve complex problems at scale and impact how millions of people access and manage money, come build with us. Southeast Asia's fintech moment starts here. About the role: This role requires relocation to Manila. We work in a hybrid format from our office in Bonifacio Global City (BGC). You'll own ML models across credit scoring, collection, and antifraud, turning data into systems that directly shape how Salmon lends and collects at scale. What you'll do: - You'll build and ship ML models across credit scoring, collection, antifraud, and sales — high-stakes, high-visibility work from day one. - You’ll work with teams across the business, including Risk, Anti-fraud, and Cross-sell - You'll take models from idea to production, then keep monitoring and improving them as real data comes in. What you'll own: - Own the end-to-end lifecycle of ML models — EDA, feature generation, hypothesis testing, production deployment, and monitoring. - Partner with Collection and Product to identify where a new or improved model would have the most leverage. - Evaluate model performance against business impact, and iterate based on what you find. - Explore and integrate new data sources, internal and external, to surface additional predictive signals. - Build models that are scalable, observable, and maintainable in production systems. What makes you a strong fit: - 2+ years of experience as a Machine Learning Engineer or Data Scientist, ideally in fintech or fast-paced product environments. - Solid foundation in classical ML techniques, fluent in Pandas, Scikit-learn, NumPy, SciPy, Matplotlib, Seaborn, Statsmodels, and gradient boosting libraries (XGBoost, LightGBM, CatBoost). - Strong Python and SQL, with experience using version control. - A strong sense of ownership and accountability. - Experience with graph neural networks or transformer models would be a plus. What we offer: Ownership and flexibility - Hybrid-first work environment - Company-provided tools and equipment - Office in Bonifacio Global City, Manila — a modern, walkable district at the centre of the Philippines' growing tech scene Health and time off - Medical insurance support for you and your family through co-funding or reimbursement, depending on your location and subject to policy limits - Access to an internal mental health support specialist - 22 vacation days, Philippine public holidays, and 15 sick days - 105 days of paid maternity leave and up to 14 days of paid paternity leave for employees relocating to Manila Relocation and family support - Relocation support for you, your family — including flights, two weeks of accommodation, visas, paperwork, and logistics - Reimbursement of eligible pet relocation expenses - USD 2,500 per year for flights home - Baby and family stipends for employees relocating to Manila: USD 1,000 per month for each child under two and USD 500 per month for each child aged two to 18 Growth and team experience - Opportunities to learn and share your expertise through internal expert meetups, external conferences, speaking opportunities, and industry publications - Company-sponsored trips to Manila to meet and work with your team in person - Regular team offsites, sports activities, and team events - High-performing teams can earn a dedicated beach house week in Southeast Asia

О ПРОЕКТЕ Команда занимается развитием внутренней AI/ML-платформы, AutoML, разработкой LLM/NLP-решений, мониторингом качества моделей на крупном финтех-проекте. ПРЕДСТОЯЩИЕ ЗАДАЧИ • Разработка и развитие ML/LLM-сценариев для production; • Работа с AutoML, NLP и RAG-пайплайнами; • Оптимизация качества и стабильности ML-решений; • Интеграция с MLOps/DE-инфраструктурой; • Быстрое прототипирование и проектирование AI-решений. ОЖИДАНИЯ ОТ КАНДИДАТА • 3+ лет опыта в DS/ML; • Хороший Python и уверенный ML-стек (Sklearn, CatBoost/LightGBM/XGBoost, Pandas, NumPy), опыт с табличными данными; • Опыт с LLM/NLP (для проекта в данном направлении); • Опыт работы с Spark/Hadoop/Hive; • Понимание production ML-процессов. БУДЕТ ПЛЮСОМ • PyTorch / DL; • Open-source contribution; • Full-stack опыт. УСЛОВИЯ РАБОТЫ • Оформление по ТК или ИП в аккредитованную ИТ-компанию; • Сильная инженерная команда и обмен экспертизой; • Гибридный или удаленный формат работы (РФ!); • ДМС со стоматологией с 1-го дня; • Предоставление техники (на выбор, по запросу).

Location: San Francisco, CA | New York City, NY | Seattle, WA 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 inference fleet serves Claude to millions of users across our own products and the world's largest cloud platforms. The stack that makes this possible is deep and tightly coupled: accelerator kernels, model servers, distributed routing, autoscaling, capacity management. Every layer affects the others, often in ways that are hard to see in isolation. The Inference System Dynamics team is responsible for understanding that whole system and holding it to a high bar across four dimensions: throughput, latency, reliability, and correctness . We measure how the fleet performs against its theoretical performance frontier, run cross-layer investigations to explain the gaps, and own the correctness checks that make sure Claude's outputs are right, not just fast, across hardware platforms and serving configurations. We don't own the individual components. We instrument and model them, find the highest-leverage opportunities across them, and partner with the owning teams to land the wins. You'll work across all four areas. One week that might mean tracing a tail-latency regression from request timing down through routing and batching into a kernel overhead; the next it might mean tightening a correctness eval so it catches an output regression introduced by a quantization change. We're looking for performance engineers who treat correctness as part of performance. Key Responsibilities Run cross-layer performance investigations across throughput, latency, and reliability, sizing the gap between actual fleet performance and theoretical rooflines, identifying root causes, and quantifying the value of closing them Own and improve the correctness evaluation pipeline that validates model output quality across hardware platforms, numerics, and serving configurations, and lead the investigation when it catches a regression Build the observability, dashboards, and modeling tools that make throughput, latency, cost, reliability, correctness, and their interactions legible across the stack Partner with kernel, serving, routing, autoscaling, and capacity teams to prioritize and land the highest-impact optimizations your analysis surfaces Ruthlessly stack-rank a large surface area of opportunities by impact and effort, and say no to the ones that don't make the cut Minimum Qualifications Hands-on performance engineering experience: profiling, roofline analysis, latency/throughput optimization, and root-cause investigation in complex production systems Proficiency in Python, with the ability to read, instrument, and contribute to large production codebases you didn’t write Solid data analysis skills (e.g. SQL, pandas, or similar) sufficient to turn raw telemetry into clear findings Ability to communicate quantitative results clearly in writing to influence priorities on teams you don't manage Genuine interest in correctness as an engineering discipline: numerics, evaluation design, regression detection Preferred Qualifications Experience with ML systems, especially training or inference infrastructure or general LLM serving stacks. Direct large-scale inference experience is a strong plus Familiarity with GPU/TPU/accelerator performance concepts (memory bandwidth, kernel overheads, quantization, collective communication). Reasoning about these matters more than having written kernels yourself Experience with reliability engineering for high-throughput services: autoscaling, load balancing, request routing, tail latency Experience with model evaluation or numerical regression-detection pipelines Experience building observability or telemetry for distributed systems Comfortable having impact through influence and evidence rather than direct ownership Representative Projects Trace a 350ms latency gap on a new accelerator platform from end-to-end request timing down to a server scheduling overhead, quantify the win, and land the fix directly or with the owning team Redesign the correctness eval gate: determine which signals reliably catch real model-output regressions versus noise, and make it the trusted release criterion across hardware backends Build a FLOPs funnel that breaks down where compute actually goes across the fleet, exposing the gap between achieved throughput and kernel rooflines Root-cause a numerical divergence between two hardware platforms to a specific kernel change, and define the acceptance threshold going forward Model the latency–cost impact of changing batch-sizing and utilization targets, and turn the result into the signal the autoscaler uses in production Deadline to apply: None. Applications will be reviewed on a rolling basis. 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: $350,000 — $850,000 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: Москва Команда занимается разработкой Disrupt-решений в сфере Безопасности Сбера Цель команды – разработка инновационных решений, проверка гипотез, посредством подготовки MVP и PoC планируемых продуктов, поддержка продуктовых команд в части оперативной разработки. Обязанности * разработка ML-алгоритмов * разработка ML-моделей * поддержка существующих AI-решений * разработка AI-Агентов * проработка AI-архитектуры внедрения решений в целевой процесс * генерация идей. Требования * высшее образование * коммерческий опыт работы разработки\\в сфере ИИ не менее 2 лет * опыт самостоятельного лидирования * готовность работы в условиях многозадачности и сжатых сроков, интенсивному обучению и повышению квалификацию * опыт работы со следующим стеком: Python, numpy, pandas, scipy, scikit-learn, XGBoost, PyTorch, OpenAI, LangChain, LangGraph, Chroma, prompt engineering, FastAPI, REST/gRPC, React, Docker, Kubernetes, GitLab. Будет плюсом: * 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 создания и использования AI-агентов. Условия * офисный формат работы, г.Москва * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * 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: Remote Workplace: Remote We are looking for a Sr. Product Data Scientist to join our growing Data team in our Product organization. This is a senior individual contributor role with broad scope across product insights, experimentation, modeling and applied analytics. The ideal candidate is not only technically strong, but also proactive in uncovering opportunities, framing insights, and ensuring leaders have the context they need to make the right calls. We are looking for this individual to bring analytical thought leadership as we continue to rapidly grow and iterate on our product offerings across Talkiatry. You’ll own projects that range from producing growth and performance analyses that guide strategic and product decisions, to designing and evaluating experiments, to improving patient engagement and clinical efficiency. You’ll be expected to communicate insights proactively, frame results in business terms, and work closely with your core cross-functional teammates (Product, Engineering and Design) as well as stakeholders across Operations, Clinical, and Finance. ABOUT TALKIATRY: Talkiatry is transforming mental health care by making high-quality psychiatry more accessible, human, and sustainable for both patients and clinicians. Co-founded by a patient and a triple-board-certified psychiatrist, we were built to solve one of healthcare’s most urgent challenges: millions of people struggle to access mental health care, while clinicians face growing administrative burden and burnout. Through our technology-powered, in-network platform, we’re changing that, creating a better experience for patients and empowering clinicians to focus on delivering exceptional care.   Today, Talkiatry is the largest dedicated psychiatry practice in the U.S., with 900+ psychiatrists, 400+ therapists, and more than 4 million patient visits delivered nationwide. At our scale, every innovation has real impact. Every workflow we improve, every technology solution we build, and every patient experience we redesign helps thousands of clinicians provide better care to hundreds of thousands of patients. We’re not just growing quickly — we’re redefining how behavioral healthcare is delivered in America.   Joining Talkiatry means joining a mission-driven team that is solving complex problems at scale, driving meaningful change in healthcare, and building the future of mental health care with compassion, innovation, and purpose. YOU WILL: Proactive Insights & Storytelling - Identify growth opportunities for the Product teams by analyzing data and understanding patient behaviors. - Help Product teams maximize impact, by working wtih PMs and engineers to understand costs and constraints, while looking at underlying data and making reasonable assumptions to size opportunities. - Identify risks by exploring data and monitoring trends to understand the impact of emerging issues before they become problems. - Frame analyses and estimates in terms of “so what” for the practice to ensure findings don’t just inform, but influence the team. - Develop regular deliverables that turn historical data into forward looking guidance for product and operational teams. - Anticipate questions our teams should be asking and bring forward insights before they’re requested. Experimentation & Measurement - Partner with Product and Operations teams to design experiments, define success metrics, and implement robust statistical evaluation frameworks. - Ensure appropriate statistical power, so results are both valid and actionable. - Analyze experiment results and establish clear post experiment communication, ensuring learnings (positive or negative) are codified and inform future product or operational decisions. Applied Analytics - Lead analyses on patient growth, clinician utilization, marketplace dynamics and more to surface actionable insights to leadership. - Translate adhoc analyses into repeatable frameworks and scalable reporting so insights don’t stay one-off, but become institutional knowledge. Collaboration - Collaborate with Data Engineering and Analytics Engineering teams to define requirements and highlight gaps, so that data pipelines reliably support advanced analytics and modeling. - Act as a thought partner to Operations, Clinical, and Finance leaders, not just answering questions, but shaping the questions we should be asking. YOU HAVE: - 4+ years of experience in data science, analytics, or related fields, with a track record of delivering measurable business impact. - Advanced proficiency in Python (pandas, scikit-learn, statsmodels and all other common data science packages) and SQL; experience with modern data warehouses (Snowflake, Redshift, BigQuery). - Strong foundation in experimental design, causal inference, and statistical methods. - Exceptional communication skills, displaying the ability to frame technical findings in a way that resonates with stakeholders. - Experience in DBT is a plus, but not required. - Experience on a Product growth team, where experimentation and opportunity identification were key aspects of the role, is a plus. - Strong applied experience in data science is essential; a Master’s or PhD in a quantitative field is a plus. WHY TALKIATRY: - Top-notch team: we're a diverse, experienced group motivated to make a difference in mental health care - Collaborative environment: be part of building something from the ground up at a fast-paced startup - Excellent benefits: medical, dental, vision, effective day 1 of employment, 401K with match, generous PTO plus paid holidays, paid parental leave, and more! - Grow your career with us: hone your skills and build new ones with our Learning team as Talkiatry expands - It all comes back to care: we’re a mental health company, and we put our team’s well-being first Talkiatry participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. only after a job offer is accepted and Form I-9 is completed. For more information on E-Verify, please visit the following: EVerify Participation https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.e-verify.gov%2Fsites%2Fdefault%2Ffiles%2Feverify%2Fposters%2FEVerifyParticipationPoster.pdf&data=05%7C01%7Cjill.steger%40talkiatry.com%7Cfe829943872e4bc8dc7b08db83d3c99d%7C803a6c90ec724384b2c01a376841a04b%7C0%7C0%7C638248717875458398%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=qFgJNzh246Js%2FFqdsb9OZgN55rg5GpsB0wjiTvkPn9w%3D&reserved=0 & IER Right to Work https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.e-verify.gov%2Fsites%2Fdefault%2Ffiles%2Feverify%2Fposters%2FIER_RighttoWorkPoster.pdf&data=05%7C01%7Cjill.steger%40talkiatry.com%7Cfe829943872e4bc8dc7b08db83d3c99d%7C803a6c90ec724384b2c01a376841a04b%7C0%7C0%7C638248717875458398%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ivUqrPtiBjGVkMzpMBSYalwvm2Zxhj%2BScqVUX2OfqUA%3D&reserved=0. At Talkiatry, we are an equal opportunity employer committed to a diverse, inclusive, and equitable workplace and candidate experience. We strive to create an environment where everyone has a sense of belonging and purpose, and where we learn from the unique experiences of those around us. We encourage all qualified candidates to apply regardless of race, color, ancestry, religion, national origin, sexual orientation, age, citizenship, marital or family status, disability, gender, gender identity or expression, pregnancy or caregiver status, veteran status, or any other legally protected status.

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s 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. You will work within a data focused function supporting Quantitative Researchers, Traders and other stakeholders across the firm. The role focuses on designing and developing financial datasets that support systematic strategies and trading decisions, with particular emphasis on market data, pricing datasets and reference data. You will combine financial market knowledge with Python and data engineering skills to build and own the automated production pipelines that create and maintain these datasets. Your future role within QRT Collaborate with Quantitative Researchers and Traders to design financial datasets that support systematic strategies and trading decisions Develop Python code to extract, clean, normalise and aggregate data from a range of financial market data sources Design, build and maintain automated data pipelines covering sourcing, extraction, transformation, validation and delivery Develop and maintain pricing and reference datasets across financial instruments and markets Investigate and resolve data quality and production issues to improve the reliability and availability of datasets Evaluate and implement new approaches to data extraction, processing and onboarding Take ownership of production data workflows and evolve them as data requirements, systems and business priorities change Your present skillset 2 to 5 years of experience in a data focused role working with financial or market data Strong understanding of financial markets and instruments, including the behaviour and characteristics of pricing and reference datasets Advanced Python programming skills, including experience with data processing libraries such as Pandas or Polars Experience designing, building and maintaining automated production data pipelines Strong data analysis and problem solving skills, with the ability to investigate data quality issues and understand their underlying causes Experience working with market data platforms and APIs from providers such as Bloomberg or LSEG is beneficial, including products such as Datastream, DataScope Select, Real Time, BPIPE or Data License Postgraduate degree in Mathematics, Physics, Engineering, Computer Science or another quantitative discipline Strong communication skills with the ability to collaborate effectively with Quantitative Researchers, Traders and other stakeholders Ability to operate effectively as priorities, systems, projects and business requirements evolve 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: Latin America Company Intro At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages . We are a well-funded startup with an enviable portfolio of clients including Anthropic , Amazon , Microsoft , Poolside , Recraft ,  and Shopify . Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin , CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA , UK , the Netherlands , Israel , Czech Republic , Serbia , and more. About the Role Technical consultants play a key role in our company, ensuring top-level delivery of our product, its correct configuration, and the deployment of tailored AI data solutions that meet our customers’ needs and deliver an exceptional experience working with us. As part of this role, you will not only design and implement data labeling pipelines but also act as a trusted technical advisor for our customers - helping them understand their data needs, discover new opportunities, and build scalable AI solutions. We are looking for a person with more than 3 years of solid technical background, who feels comfortable working in technical environments, solving data-related tasks using Python and AI, and communicating directly with customers. You should be a confident communicator able to engage with both technical and executive stakeholders and collaborate closely with our commercial team. Responsibilities 1. Client Ownership & Communication Act as the primary technical point of contact for customers across technical and executive stakeholders. Lead discovery conversations to deeply understand client goals, problems and quality criteria. Translate client needs into clear, actionable solution designs and delivery plans. Advise customers on best practices in data collection, data quality, evaluation, and model training workflows. Set expectations proactively, communicate progress regularly, and manage risks and trade-offs transparently. Identify expansion opportunities and additional ways Toloka can create value through data and AI solutions. 2. Solution Design & Delivery Design end-to-end data solutions using Toloka’s platform, selecting appropriate components, workflows, and quality controls. Configure data labeling components and quality controls, develop user interfaces and AI-driven tooling (e.g. agentic systems, RAGs, synthetic data generation), and integrate them into end-to-end automated pipelines for AI training and evaluation. Run experiments and pilots to validate quality, throughput, and cost assumptions. Lead technical execution during delivery, coordinating internal teams and external stakeholders as needed. Ensure solutions meet agreed quality, performance, and scalability requirements. 3. End-to-End Ownership & Project Management Own delivery outcomes holistically - including technical performance, quality, timelines, and financial efficiency. Monitor key KPIs (e.g. throughput, quality metrics, Gross Margin, Contribution Margin) and act on deviations. Prioritize work based on customer impact and business value. Analyze data to identify failure modes, inefficiencies, and opportunities for improvement. Continuously optimize solutions through iteration, automation, and adoption of new technologies. Troubleshoot delivery, process, or technical issues in collaboration with support, infrastructure, and product teams. Drive solutions toward stable operation with minimal ongoing maintenance. Requirements Core Experience Experience as a Solution Engineer, Technical Solutions Engineer, Data Scientist, Data/Systems Analyst, or Technical Project Manager. Proven experience owning projects end-to-end, including scoping, delivery, and stakeholder management. Direct experience working with external customers on technical projects (requirements gathering, delivery, iteration). Technical Skills Strong Python skills for data manipulation (e.g. NumPy, pandas), natural language processing (e.g. NLTK, spaCy), and building lightweight web services or tools (e.g. FastAPI, Flask). Solid understanding of ML concepts and data workflows; familiarity with LLMs and prompt engineering is a strong plus. Experience designing multi-stage pipelines and complex systems. Understanding of software development fundamentals: version control, testing, MVPs, iterative development etc.. Bachelor’s or Master’s degree in Data Science, ML/AI, Software Engineering, or a related quantitative field such as Physics or Applied Mathematics, with strong analytical foundations. Ability to reason about trade-offs between quality, speed, cost, and scalability. Communication & Ownership Excellent English communication skills (B2+), with the ability to explain complex technical concepts to non-technical audiences. Confidence working with data engineers, ML engineers, and researchers from leading tech companies. Strong ownership mindset: comfortable being accountable for outcomes, not just tasks. Ability to manage multiple projects in fast-paced, ambiguous environments. Nice to have Experience with crowdsourcing, expert workflows, or large-scale data labeling. Experience working on ML training, evaluation, or agentic systems. Familiarity with quality frameworks, audits, or data validation pipelines. [Important Notice] Scam Alert Regarding Fake Job Postings It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants.Please be aware: Official Communication: Our recruiting team will only contact you from an official " toloka.ai " email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc,  or other personal or seemingly business email accounts. Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it. Thank you for your vigilance!

Location: United Kingdom; Moldova We need someone who understands data deeply and uses Python to wrangle it — not a platform engineer, not a pure pipeline builder, but a data specialist who's comfortable with research, investigation, and the unglamorous work of making messy energy market data actually usable. You'll spend significant time on tasks like: mapping BM units to power plants and fuel types, reconciling legacy data formats with current ones, ensuring consistency between different Elexon message types, and cleaning time-series data (outliers, gaps, overlaps). Some of this requires genuine investigation — cross-referencing sources, making judgment calls, documenting edge cases. There's no API that solves these problems for you. Python is your primary tool (Pandas, Numpy, standard libraries) to minimise manual effort, but you should be comfortable that some detective work is unavoidable. If you find satisfaction in truly understanding a dataset's structure and quirks — rather than just piping data through and hoping for the best — this role is for you. Data Mapping and Research • Map BM units from Elexon to their corresponding power plants, substations, and fuel types — combining API data, public registers, and manual research • Map substations to ETYS zones and grid supply points • Build and maintain reference/master datasets that link identifiers across disparate sources (Elexon, National Grid ESO, TEC register, etc.) • Document mappings, assumptions, and known limitations clearly for downstream users Data Reconciliation and Consistency • Reconcile legacy data formats with current formats (e.g., historical operational data stored in different schemas or granularities) • Ensure consistency between different Elexon message types — understand the market data structure well enough to know why BOALF, BOD, and DISBSAD might not perfectly align and how to handle it • Investigate discrepancies between data sources and determine authoritative values Data Cleaning and Quality • Clean time-series data: detect outliers (price spikes, meter errors), fill gaps appropriately, resolve overlapping or duplicate timestamps • Develop reusable Python-based cleaning routines that can be applied across datasets • Understand why data quality issues occur (settlement reruns, late submissions, format changes) not just patch them Pipeline Development (Supporting the Above) • Write and maintain Python data grabbers for energy market APIs • Build dbt models to transform raw data into clean, analysis-ready datasets • Orchestrate workflows via GitHub Actions • Design PostgreSQL schemas that reflect your understanding of the domain Requirements • Strong Python skills for data work — you're fluent with pandas, comfortable writing clean, testable code, and can build reusable data processing logic. This is not an Excel role. • Solid SQL skills — complex queries, window functions, CTEs in PostgreSQL • Experience with messy, real-world data — you've done reconciliation, cleaning, or mapping work before and understand it's not always automatable • Methodical and detail-oriented — you notice inconsistencies and want to understand root causes • Good documentation habits — you know that undocumented mappings and assumptions are technical debt • Self-directed — you can own ambiguous problems, do your own research, and communicate findings clearly Nice to Have • Experience with energy, utilities, or market data (any geography) • Familiarity with UK energy markets, Elexon data, or grid operations • dbt experience for transformation pipelines • Exposure to time-series data challenges (irregular timestamps, gaps, restatements) Highly Desirable — Agentic AI Coding Experience We value candidates who can build software using agentic AI coding systems. This is fundamentally different from using code completion tools or chat-based assistants. Not What We're Looking For • Platform/infrastructure engineers who prefer to stay above the data layer • People who expect clean, well-documented data as input • Those uncomfortable with research, ambiguity, or "manual" investigation work Practicalities • Remote-first with async collaboration (Slack, GitHub, documented decisions) • Core overlap with UK business hours expected (at least 4 hours daily) • Competitive compensation based on location and experience Benefits Plenty of opportunities for learning and professional growth B2b contract with a paid vacation

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

Location: Abu Dhabi, UAE; Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Position Overview We are seeking a highly analytical and data-driven Risk Strategy Specialist to design, optimize, and scale our risk automation framework. In this role, you will be responsible for protecting our platform against peer-to-peer transaction risks, including account takeovers, social engineering scams, money laundering, and payment velocity abuse. You will combine a strong Data background with hands-on coding in Python and SQL to detect subtle fraud patterns across massive transaction ecosystems. Key Responsibilities Pattern Detection & Behavioral Analysis: Mine high-volume, multi-dimensional transaction and event logs to uncover emerging fraud vectors, synthetic networks, collusion rings, and anomalous transfer patterns. Risk Strategy Development: Design, implement, and iterate real-time decisioning rules and risk policies (e.g., dynamic transfer limits, step-up authentication, cooling-off periods) to mitigate risk while preserving a frictionless user experience. Advanced Data Analysis: Write production-grade, optimized SQL and Python scripts to analyze network graphs, transaction velocity, device signals, and user interaction metrics. Model Integration & Experimentation: translate models into operational strategies, establish decision thresholds, and run A/B tests to quantify strategy performance. Post-Mortem & Loss Mitigation: Perform quantitative root-cause analysis on fraudulent transactions, chargebacks, and ATO incidents to plug strategy gaps and minimize direct financial losses. Risk Performance Monitoring: Build and maintain automated dashboards and KPI tracking systems Qualifications & Requirements Core Requirements: 3+ years of experience in risk strategy, transaction monitoring, payment fraud analysis, or trust & safety within Fintech, Banking, or Digital Marketplaces. Advanced SQL Skills: Proficient in complex joins, window functions, CTEs, and optimizing queries on large-scale distributed databases (e.g., Snowflake, BigQuery, Redshift). Proficient in Python: Strong experience using Python libraries ( pandas , numpy , scikit-learn , networkx ) for data manipulation, exploratory data analysis, and rule automation. Pattern Detection & Analytics: Proven track record of identifying complex fraud networks, transaction velocity anomalies, or multi-account abuse patterns. Preferred Experience & Education: Educational Background: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Economics, or a related quantitative field ( Data Science background strongly preferred ). Direct experience with payment mechanisms , real-time settlement rails, card-to-card transfers, or digital wallets. Hands-on experience with graph theory/network analysis (identifying linked accounts, shared device fingerprints, IP linkages). Familiarity with machine learning workflows, rule engine architectures, and dynamic risk-scoring frameworks. Strategic Problem Solver: Comfortable tackling ambiguous, rapidly evolving risk problems in a fast-paced environment. Cross-Functional Communication: Excellent at translating data science insights and technical risk concepts into strategic recommendations for business stakeholders. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Location: New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . About the role Turing builds the training and evaluation data powering the world’s leading frontier AI labs. As these labs push the frontier, they bring us their newest models and ask the critical question: how does our model perform against your benchmark datasets, where does it fail, and what data will make it climb the hill? As a Field Engineer, AI Labs , you are the technical face of Turing to frontier research teams. You sit at the exact intersection of client-facing solutions engineering and hands-on AI evaluation. When a frontier lab provides a new model endpoint, you wire it up, run comprehensive evals across Turing’s datasets, synthesize raw performance metrics into actionable intelligence, and present those findings directly to client researchers and technical leaders. This is not a pure research engineering seat and not a traditional forward-deployed IT role. It is a high-velocity, high-agency solutions engineering role for a technically fluent, dependable builder who thrives on talking to customers, running benchmarks across model APIs, and packaging last-mile data deliveries with extreme precision. Why this role matters You will work directly with research scientists and technical executives at top AI labs (such as xAI, Anthropic, OpenAI, and emergent frontier labs). Every eval you run and every benchmark report you write directly influences how frontier labs evaluate model capabilities, uncover failure modes, and procure the pre-training and post-training data required for next-generation intelligence. What you’ll own Evaluation & Benchmarking Connect frontier model APIs and inference endpoints (OpenAI, Anthropic, AWS Bedrock, vLLM, private client gateways) into evaluation harnesses. Execute large-scale benchmark runs across proprietary Turing datasets (reasoning, coding, multimodal, agentic environments, and GDP Val). Analyze eval results, isolate failure cases, detect model behavioral drift, and identify the exact data distributions needed to address capability gaps. Technical Pre-Sales & Client Engagement Serve as the technical counterpart to sales leads on calls with frontier AI labs and enterprise AI teams. Translate complex evaluation metrics into compelling, high-signal reports, client presentations, and technical collateral. Answer technical questionnaires and RFIs from lab researchers regarding data design, task curation, difficulty stratification, and rubrics. Surface lab feedback and emerging benchmark requirements back to internal R&D and dataset design teams. Internal Data Systems & Catalog Stewardship Navigate and operate Turing’s internal data infrastructure (DataOS, Data Hub, and task catalogs) to query, manipulate, and move data pipelines. Slice and curate custom data subsets based on specific difficulty thresholds, benchmark rubrics, or top-performing data points. Audit data provenance and maintain up-to-date specifications across Turing's public catalog and internal dataset inventories. Packaging & Last-Mile Delivery Own last-mile delivery, schema alignment, and packaging so that data delivered matches client technical specifications flawlessly. Work closely with engineering and quality leads to verify that all data deliverables adhere to rigorous validation standards before client handoff. What you bring Required 1 to 5 years of professional experience in data science, AI/ML engineering, solutions engineering, or data analytics with a demonstrated transition into generative AI. Strong hands-on Python proficiency: working with REST/gRPC model APIs, inference endpoints (OpenAI, Anthropic, Bedrock, vLLM), pandas, and SQL. Practical experience with model evaluation, benchmark design, or LLM-as-a-judge pipelines. You know how benchmarks are structured, scored, and debugged. High agency and a scrappy, startup mindset: you have owned projects end-to-end, delivered under tight deadlines, and thrive in fast-paced environments where playbooks are being built in real time. Exceptional written and verbal communication: ability to walk research scientists through technical evaluation metrics and command confidence on commercial calls. Comfort working with command-line tools, internal tooling, and data manipulation workflows. Preferred Prior experience at an early-stage AI startup or high-growth technology company where you wore multiple hats across engineering and customer support. Hands-on experience with evaluation harnesses and agent benchmarks (e.g., Harbor, Terminal-Bench, SWE-bench, Inspect) or agentic workflows. Experience fine-tuning models (e.g., LoRA/QLoRA), working with open-weights models, or conducting multimodal evaluations. Familiarity with data quality control, task verification, or synthetic data generation pipelines. How we work High ownership, low ego: You own the last mile from intake to client handoff. The outcome matters more than who gets credit. Technical fluency with commercial empathy: We don't hide behind jargon. We present clear, honest numbers to lab researchers and act as their trusted technical partners. Rigorous data integrity: Provenance, versioning, and reproducibility come first. What we benchmark is what the client gets. Location & Work Model Location: United States. Strong preference for candidates based in the San Francisco Bay Area (for regular interaction with local AI labs and team hubs); remote within the US considered for exceptional candidates. Employment Type: Full-time standard employee. Compensation & Benefits The annual base salary range for this full-time position is $175,000 – $232,000 USD . In addition to base salary, this role is eligible for equity, performance incentives, and comprehensive company benefits. Individual compensation is determined by job-related skills, experience, qualifications, and relevant business considerations. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

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

Location: USA Company Intro At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages . We are a well-funded startup with an enviable portfolio of clients including Anthropic , Amazon , Microsoft , Poolside , Recraft ,  and Shopify . Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin , CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA , UK , the Netherlands , Serbia , and more. About the Role Technical consultants play a key role in our company, ensuring top-level delivery of our product, its correct configuration, and the deployment of tailored AI data solutions that meet our customers’ needs and deliver an exceptional experience working with us. As part of this role, you will not only design and implement data labeling pipelines but also act as a trusted technical advisor for our customers - helping them understand their data needs, discover new opportunities, and build scalable AI solutions. We are looking for a person with more than 3 years of solid technical background, who feels comfortable working in technical environments, solving data-related tasks using Python and AI, and communicating directly with customers. You should be a confident communicator able to engage with both technical and executive stakeholders and collaborate closely with our commercial team. Responsibilities 1. Client Ownership & Communication Act as the primary technical point of contact for customers across technical and executive stakeholders. Lead discovery conversations to deeply understand client goals, problems and quality criteria. Translate client needs into clear, actionable solution designs and delivery plans. Advise customers on best practices in data collection, data quality, evaluation, and model training workflows. Set expectations proactively, communicate progress regularly, and manage risks and trade-offs transparently. Identify expansion opportunities and additional ways Toloka can create value through data and AI solutions. 2. Solution Design & Delivery Design end-to-end data solutions using Toloka’s platform, selecting appropriate components, workflows, and quality controls. Configure data labeling components and quality controls, develop user interfaces and AI-driven tooling (e.g. agentic systems, RAGs, synthetic data generation), and integrate them into end-to-end automated pipelines for AI training and evaluation. Run experiments and pilots to validate quality, throughput, and cost assumptions. Lead technical execution during delivery, coordinating internal teams and external stakeholders as needed. Ensure solutions meet agreed quality, performance, and scalability requirements. 3. End-to-End Ownership & Project Management Own delivery outcomes holistically - including technical performance, quality, timelines, and financial efficiency. Monitor key KPIs (e.g. throughput, quality metrics, Gross Margin, Contribution Margin) and act on deviations. Prioritize work based on customer impact and business value. Analyze data to identify failure modes, inefficiencies, and opportunities for improvement. Continuously optimize solutions through iteration, automation, and adoption of new technologies. Troubleshoot delivery, process, or technical issues in collaboration with support, infrastructure, and product teams. Drive solutions toward stable operation with minimal ongoing maintenance. Requirements Core Experience Experience as a Solution Engineer, Technical Solutions Engineer, Data Scientist, Data/Systems Analyst, or Technical Project Manager. Proven experience owning projects end-to-end, including scoping, delivery, and stakeholder management. Direct experience working with external customers on technical projects (requirements gathering, delivery, iteration). Technical Skills Strong Python skills for data manipulation (e.g. NumPy, pandas), natural language processing (e.g. NLTK, spaCy), and building lightweight web services or tools (e.g. FastAPI, Flask). Solid understanding of ML concepts and data workflows; familiarity with LLMs and prompt engineering is a strong plus. Experience designing multi-stage pipelines and complex systems. Understanding of software development fundamentals: version control, testing, MVPs, iterative development etc.. Bachelor’s or Master’s degree in Data Science, ML/AI, Software Engineering, or a related quantitative field such as Physics or Applied Mathematics, with strong analytical foundations. Ability to reason about trade-offs between quality, speed, cost, and scalability. Communication & Ownership Excellent English communication skills (B2+), with the ability to explain complex technical concepts to non-technical audiences. Confidence working with data engineers, ML engineers, and researchers from leading tech companies. Strong ownership mindset: comfortable being accountable for outcomes, not just tasks. Ability to manage multiple projects in fast-paced, ambiguous environments. Nice to have Experience with crowdsourcing, expert workflows, or large-scale data labeling. Experience working on ML training, evaluation, or agentic systems. Familiarity with quality frameworks, audits, or data validation pipelines. What we can offer Full-time independent contractor engagement (B2B) through the Ontop contractor platform , working via your own company or business entity; Flexible, fully remote schedule ( 40 hours per week ); Work at the leading edge of AI development, alongside a dedicated and dynamic team of experts; Projects with customers that are AI industry leaders and well-known household names; Friendly community. [Important Notice] Scam Alert Regarding Fake Job Postings It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants.Please be aware: Official Communication: Our recruiting team will only contact you from an official " toloka.ai " email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc,  or other personal or seemingly business email accounts. Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it. Thank you for your vigilance! To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice .

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

Location: Tbilisi, Georgia Workplace: remote Novakid is on a mission to build the best online education platform for kids worldwide. We already have over 100,000 students and 4,500 teachers in 15+ countries across Asia, Europe and Latin America, and we want to grow faster. We are looking for a Product Analyst for our Growth squad. The squad owns the product side of the funnel, from the first visit to the first payment. You will spend most of your time as its analyst, working alongside marketing analytics, who own channels and attribution. What you will do: Own the funnel metrics from visit to payment and shape the squad’s roadmap with the PM Run the experiment cycle: decide whether an idea needs a test, size it on historical data, design and read A/B tests in GrowthBook, and use region-level comparisons where a classic A/B does not fit Build and maintain dbt models with tests and code review, and Metabase dashboards on top of them Keep funnel tracking reliable by defining events and data contracts with backend engineers Develop and support our AI analytics assistant: own the Growth domain in its knowledge base, review its answers and fix what it gets wrong Take requests from other teams through the analytics team’s shared intake Our stack: BigQuery, dbt, Metabase, GrowthBook, Bloomreach, Python, git with pull-request review. Claude Code/Cursor are part of daily work. You have 3+ years as a Product Analyst, preferably in B2C or a fast-growing company Excellent SQL and hands-on experience building data marts, ideally in dbt Python for analysis (pandas, numpy, scipy or statsmodels) A/B testing from design to evaluation: power, variance reduction, multiple-testing correction A solid grasp of funnel and unit economics in a subscription business The habit of turning analysis into a decision and explaining it clearly English B1+ for business communication Nice to have Causal inference or uplift modeling Applied ML in a business context Experience building or evaluating LLM-based tools What you get Fully remote work A chance to shape the future of AI-driven education Ownership of the acquisition funnel and its metrics, not a ticket queue Dedicated time for analytics infrastructure, not only squad requests A fun, dynamic team that loves building innovative products Unlimited holidays – because we trust you to deliver Bonuses and stock options – we grow together

Location: Ho Chi Minh City WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. About WorldQuant BRAIN: BRAIN is a group within WorldQuant similar to a traditional B2C fintech setup. Our mission is to simplify quant finance and provide global remote-work opportunities to participants, while they learn quant finance, AI and ML concepts. WorldQuant BRAIN provides an advanced crowdsourcing platform for external participants to contribute signals, data, and more. What You'll Do: Develop backend application services and APIs. Integrate systems with AWS and external cloud services. Optimize backend components for speed and scalability. Implement and manage caching, queuing and background processing. Participate in code reviews, technical design discussions and architecture decisions. Be an active member of an agile engineering team who is continuously looking to improve team performance. Work with leading cloud technologies (such as AWS, GCP). Work with leading open-source technologies (such as MySQL, PostgreSQL, ELK stack, Sentry, Redis, Git, etc.). Leverage modern AI tools and practices to increase developer productivity. Participate in periodic on-call duties. What You’ll Bring: 2+ years demonstrated experience developing scalable and robust software. Passion about software engineering, be strongly driven to build and run real-world applications at scale. Eagerness to learn and introduce new technologies. Be curious about what's happening in the tech world. Excellent coding skills, solid understanding of the broad Python ecosystem including Numpy, Pandas and Asyncio. Expertise in Python web frameworks such as Django, DRF, Flask or others. Experience with SQL databases (MySQL, PostgreSQL), including schema design, query optimisation and migrations. Experience with microservices, caching tools, data visualization, log collection and aggregation, search, queuing systems. Experience with Linux environment and shell scripting. Excellent debugging and problem solving skills. What We Offer: Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday We offer a strong culture of learning and development: training courses, library, speakers, share and learn events Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people Premium Health Insurance and Employee Assistance Program Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family Team building activities every month: Local engagement events, Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc. Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams Happy-hour with tea break, snacks and meals every day in the office! #LI-VP1 By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved. WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

Location: Limassol; Nicosia Workplace: hybrid The Role:  We are looking for an experienced Data Scientist to join our Data Science department. In this role, you will work hands-on on advanced analytics and machine learning projects, leveraging large datasets to build impactful, production-ready solutions.  Ideal for someone who enjoys solving complex problems, building models end-to-end, and driving data-driven decision-making The main responsibilities of the position include: Design, develop, and review machine learning models and advanced analytics solutions Apply statistical analysis and data mining techniques to extract meaningful insights from large datasets Ensure high standards in data preparation, feature engineering, model evaluation, documentation, and code quality Collaborate with cross-functional teams including data engineers, software engineers, product owners, and business stakeholders Present insights, analysis results, and recommendations to both technical and non-technical audiences Ensure adherence to best practices in data quality, model monitoring, version control, and reproducible analytics Contribute to the development of the department’s data science strategy and identify opportunities where data science can deliver business value Main requirements: University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or a related quantitative field At least 3 years of experience in data science, machine learning, or advanced analytics Strong programming skills in Python and experience with Pandas, NumPy, and similar data analysis libraries Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly Strong knowledge and exposure to Machine Learning Knowledge of Recommendation Systems will be considered a plus Solid understanding of statistics and data mining techniques Experience working with relational and non-relational databases Strong analytical thinking, problem-solving ability, and attention to detail Excellent communication skills and the ability to work collaboratively in a team environment Benefit from: Attractive remuneration package Private health insurance Corporate pension fund Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Bring It to Life – Role-Specific Take-Home Task Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy and Data Protection Notice and the Confidentiality Undertaking.