Location: Minsk; Warsaw; Tbilisi; Chișinău; Buсharest; Belgrade; lisbon
Workplace: hybrid
IDT is expanding its AI Lab and seeking a hands-on, highly experienced Senior Data Scientist with a proven track record of building new ML models from scratch and deploying them into real-time production. You will tackle complex problems across fraud prevention, payment risk, transaction scoring, personalization, and financial forecasting using large-scale transactional datasets. You will own the full modeling lifecycle — from problem framing through to production monitoring.
Key Responsibilities:
ML & Predictive Modeling:
Design and build new models from the ground up (gradient boosting, neural networks, ensembles, anomaly detection) for anti-fraud, risk assessment, and personalization; maintain rigorous validation practices to prevent data leakage and overfitting.
End-to-End & MLOps:
Partner with Data Engineering and MLOps to operationalize models in production (batch and real-time/low-latency); build training, experiment tracking (MLflow), and model/data drift monitoring pipelines.
Experimentation & Business Impact:
Design A/B tests and statistical evaluations to measure model performance against key business metrics (reduced fraud losses, transaction acceptance rates, decision latency).
R&D & Technical Leadership:
Explore emerging techniques (LLMs/GenAI, graph-based methods), establish engineering best practices, and mentor fellow team members.
Requirements (Must-Have):
Experience:
5+ years of hands-on experience in Data Science / ML, with a strong focus on
designing and building new ML models from scratch
and delivering them into production with measurable business impact.
English:
B2+ (Upper-Intermediate or higher)
— fluent written and spoken communication for technical discussions and daily collaboration with an international team.
Math & Modeling Foundations:
Deep understanding of statistics, probability, and validation methodologies; practical experience handling class imbalance, model calibration, and anomaly detection.
Tech Stack:
Python:
Advanced proficiency (Scikit-learn, Pandas, NumPy);
Deep Learning:
Hands-on experience with PyTorch or TensorFlow;
SQL:
Complex queries and large-scale data manipulation;
MLOps Tools:
Experiment tracking and model lifecycle management (MLflow, ClearML, etc.).
Education:
Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field.
Nice-to-Have:
Domain experience in FinTech, Payments, or Fraud Prevention: real-time transaction scoring and low-latency inference.
Experience with cloud data platforms (Snowflake), Feature Stores, and event-driven architectures.
Background in time-series forecasting, graph neural networks, Explainable AI (XAI), or applied LLM solutions.
Master’s degree or Ph.D. in a quantitative discipline.
We offer you:
Remote b2b or hybrid (Belarus-Moldova) work opportunity!
Stable job with long-term growth perspective.
Competitive salary with annual performance review.
Really good hardware.
An exciting and challenging job with talented people around.
Continuous learning and career growth opportunities.
Compensation for professional training, seminars, and conferences.
Referral program – get rewarded for helping us grow the team with talented people.
Company-supported English classes to enhance your professional growth.
More perks for the Minsk and Chisinau office employees.
A few words about us:
IDT Corporation is a global communications company founded in 1990 and headquartered in Newark, New Jersey. We are industry leaders in prepaid communication and payment services and one of the largest international voice carriers. We are listed on the NYSE, employ over 1800 people across 20 countries, and have over $1.5 billion in revenues.
IDT is not ”another big IT corporation”— we encourage and support in-house entrepreneurs in developing their ideas into business actions.
Our flagship brand, BOSS Revolution, offers Money Transfer, International Calling, and Mobile Top-Up services and supports IDT’s mission of enabling people to keep in touch and share resources with family and friends worldwide.
If you're looking for a company that will give you the maximum flexibility in choosing a location to work, this opportunity is for you!
Location: Chicago, IL, USA; New York, NY, USA; San Francisco, CA, USA
About the role
Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring AI/ML Engineers across several teams, Trust & Safety, Lending, Growth, and Foundation Models, and you'll be matched with the team where your background, experience and interests fit best.
In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into decisions that protect members from fraud, expand access to credit, and power the personalized experiences and marketing that help millions of members get more out of products like MyPay, Instant Loans, and SpotMe — along with the foundational models the rest of our teams build on. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters.
In this role, you can expect to
Build, train, and deploy deep learning and classical ML models on large-scale financial, transactional, and behavioral datasets
Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live
Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining
Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one
Connect model performance to member outcomes and business metrics, and use experimentation to prove impact
Contribute to the shared ML platform, tooling, and standards that the rest of the team builds on
Help identify where AI/ML creates measurable impact for members — and where a simpler answer is the better one
To thrive in this role, you have
Experience building and deploying deep learning models in production, with a solid grasp of architecture choice, training dynamics, and evaluation — and the judgment to model design choices
Solid machine learning fundamentals: classical modeling, evaluation design, and knowing which metric actually answers the question in front of you
Hands-on experience across the end-to-end ML lifecycle — training, experimentation, optimization, deployment, and monitoring
Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew
Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark
Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy
The ability to operate independently in ambiguous environments, and to communicate clearly with both technical and non-technical partners
Nice-to-Have
Experience in any one of these is a plus, and helps us match you to the right team.
Trust & Safety
— fraud, risk, abuse detection, or adversarial modeling
Lending
— credit or underwriting models, and familiarity with model governance, explainability, and fairness requirements
Growth
— personalization, recommendation, marketing measurement, or experimentation at scale
Foundation Models
— transformers on tabular or semi-structured data, large-scale pretraining, ML platform work, or applied research with a publication record
#LI-DA1 #LI-Onsite
Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
Wage Notice
$125,000
—
$292,000 USD
A little about us
At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential.
We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.
We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress.
We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential.
Because if we don't—who will?
*Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC.
What we offer for our full-time, regular employees
🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location.
💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees.
✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life.
🏝 Generous vacation policy and company-wide paid days off
🫂 1% of your time off to support local community organizations of your choice
👟 Annual wellness stipend to use towards eligible wellness related expenses
👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents
👪 Access to family planning reimbursement
💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress
We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals.
Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact:
accommodations@chime.com
.
To learn more about how Chime collects and uses your personal information during the application process, please see the
Chime Applicant Privacy Notice
.
Задачи:
— участвовать в проектировании RAG-архитектуры под B2B-кейсы: помогать выбирать источники данных, настраивать ingestion, chunking, базовые стратегии retrieval (dense/hybrid) под руководством более опытных коллег;
— настраивать LLM/агентов под предметную область: реализовывать промпты, подключать инструменты (tool calling), работать с контекстом и базовой памятью;
— реализовывать POC/POV на данных клиента, проводить итерационные улучшения на основе метрик и обратной связи;
— строить Data Ingestion пайплайны с OCR;
— реализовывать evaluation-пайплайны: генерация тестовых наборов, запуск auto-eval, участие в human-eval;
— считать и анализировать ключевые метрики (accuracy, coverage, latency, user success rate), готовить отчеты для команды;
— участвовать в настройке мониторинга: логирование, базовые алерты, анализ неуспешных кейсов и их фиксы;
— участвовать в интеграции с инфраструктурой (Kubernetes, облако), работать с метриками и логами;
— участвовать в нагрузочном тестировании для оценки скорости инференса и необходимых ресурсов.
Требования:
— опыт работы с Python (pandas, PyTorch/TF, API LLM);
— опыт работы в ML/DS/NLP от двух лет;
— опыт работы с LLM/RAG;
— понимание полного цикла ML-разработки;
— практический опыт работы с RAG: настройка retrieval, работа с embedding-моделями, векторными БД (FAISS, Qdrant, Pinecone и др.);
— понимание базовых техник улучшения качества (reranking, filtering, prompt tuning);
— опыт работы с агентными фреймворками (LangChain / LangGraph / LlamaIndex / ADK и др.);
— базовое понимание agentic-подходов и tool calling;
— опыт prompt engineering и настройки LLM под задачи;
— базовый опыт fine-tuning (или понимание подходов: LoRA, QLora, instruction tuning);
— понимание оптимизации инференса (на уровне использования инструментов: vLLM, quantization и др.);
— опыт работы с популярными ML фреймворками: tranformers, vllm, sglang, pytorch;
— SQL, базовое понимание работы с данными и пайплайнами;
— опыт деплоя сервисов (Docker, FastAPI), базовое понимание Kubernetes/облака;
— навыки логирования, мониторинга и базовых A/B-экспериментов;
— опыт работы с evaluation для ML/LLM (auto-метрики + участие в ручной оценке, LLM-as-Judge).
Location: Remote
Workplace: Remote
ABOUT US
Launched in 2019, Constructor is an AI-first ecommerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains.
As a Senior Machine Learning Engineer in the Search Quality team, you will improve the e-commerce experience for hundreds of millions of users across the world by building the systems that power relevance for global retailers - from fashion and grocery to electronics and hardware.
The mission is to measure search quality, push it higher, and catch degradations before the user does. You will achieve this through a blend of fine-tuned LLMs for relevance judgment, real-time models, and deep offline analysis of query logs.
ABOUT THE JOB
Your primary focus will be relevance evaluation and quality improvements:
- LLM-based evaluation. We fine-tune our own models to assess relevance. This involves teaching the model to understand query intent, represent items from messy catalog data, and align model judgments with real user behavior.
- Real-time quality in production. Reranking, filtering, signal computation. Latency is a strict requirement, so quality vs speed tradeoff is constant.
- Automated quality monitoring and agentic insights. Pipelines to detect degradations and find underperforming patterns. Agent-based systems that generate actionable recommendations for the product data and search configurations.
WHAT MAKES THIS INTERESTING
- Multi-domain, multi-language, at scale - 40+ languages, 20+ domains. The models need to generalize across all of them - without per-customer rules or overrides.
- No universal ground truth. A grocery retailer and a fashion retailer may have different perceptions on what "relevant" means.
- Efficiency at scale. Optimizing and scaling LLM inference across our entire customer base.
REQUIREMENTS
- 4+ years shipping production ML systems
- Experience with search, information retrieval, or recommendation systems
- Hands-on experience with fine-tuning, evaluation frameworks, and scaling LLM deployments
- Strong Python and PyTorch. Fluency in SQL and data orchestration tools (Spark, Airflow)
- Experience designing and running A/B tests to validate model impact
- Excellent English communication skills
- Experience collaborating in cross-functional teams (ranking, product, data engineering)
BENEFITS
- 🧠 Work with smart and empathetic people who will help you grow and make a meaningful impact.
- 🎉 Regular team offsite events to connect and collaborate.
- 🌎 Fully remote team - choose where you live.
- 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year.
- 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office.
- 💻 Apple laptops provided for new employees.
- 🧑🎓 Training and development budget for every employee, refreshed each year.
- 👪 Maternity & Paternity leave for qualified employees.
- 💵 Base salary: $80k–$120K USD, depending on knowledge, skills, experience, and interview results
- 📈 Stock options - offered in addition to the base salary
DIVERSITY, EQUITY, AND INCLUSION AT CONSTRUCTOR
At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group.
Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications.
How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice https://constructor.com/recruitment-privacy-notice. After that period your data will be deleted or anonymized.
Обязанности:
• разработка и сопровождение AI-агентов для автоматизации процессов оценки кредитного риска
• интеграция LLM и ML-моделей в агентные пайплайны (оркестрация, tool-calling, memory, RAG)
• проектирование агентных архитектур: определение инструментов, стратегий и логики принятия решений
• написание технической документации: описание агентов, регламенты, схемы взаимодействия.
Требования:
• опыт разработки на Python от 3 лет, особенно в контексте написания бизнес-логики или скриптов автоматизации
• уверенное и архитектурных паттернов
• опыт работы с агентными фреймворками: LangChain, LangGraph, AutoGen, CrewAI или аналоги
• понимание ML (train/inference): xgboost, catboost, lightgbm, pytorch — опыт интеграции моделей в продуктовые системы
• работа с Python-библиотеками pyspark / pandas / numpy для анализа данных
• опыт работы с HTTP(S), RESTful API (интеграция агентов и моделей с внешними сервисами)
• опыт работы с Docker; базовые знания Kubernetes и Helm
• опыт работы с Git
Условия:
• комфортный современный офис рядом с м. Кутузовская
• график работы- гибрид
• ежегодный пересмотр зарплаты, 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
• бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров
• вознаграждение за рекомендацию друзей в команду Сбера.
Location: New York Office
Workplace: Hybrid
Taktile empowers financial institutions to transform into truly AI-native organizations. We’re growing rapidly with enterprise customers across banks and insurance companies, and we’re looking for a Lead Solutions Engineer in our NYC headquarters.
As a Lead Solutions Engineer focused on enterprise pre-sales, you are the technical bridge between our enterprise prospects and our AI-powered decisioning platform. You will partner with the Sales Team to architect AI-driven solutions for the world's most innovative financial institutions. Your mission is to secure the technical win by demonstrating how Taktile leverages Generative AI and advanced ML to solve complex credit, risk, and fraud challenges. You are a trusted advisor to our customers and help them achieve their strategic goals and realize value by using Taktile in their decisioning tech stack.
If you are passionate about cutting-edge technology, stay up to date on the latest AI developments, and have a few years of hands-on experience with Python, APIs, and modern AI models in customer-facing environments - all while thriving in a an awesome team that empowers you to grow, then we think you'll love this job!
About You
- You excel at navigating complex Enterprise organizations with stakeholders across different levels of seniority and including both technical stakeholders in an organization (e.g. Principal Engineers, Data Scientists) as well as business stakeholders (e.g. Risk Managers, Credit Analysts).
- You have 3+ years of hands-on experience writing production Python code
- You are curious and customer-centric. You enjoy learning about our customers’ and prospects’ businesses and helping them solve challenges.
- You are able to plan and manage the technical scope of Proof of Concepts (POCs) and technical evaluations. You excel at managing multiple high-stakes prospects simultaneously while partnering with Sales to drive deals to close
- You are humble and have a growth mindset, with a willingness to learn new skills and methodologies and bring best practices into our business.
- You are collaborative and work well with your peers in Marketing, Sales, Product, Engineering and the Customer Success team.
- You have a proven track record of supporting high-contract-value enterprise deals. You understand that winning an enterprise deal requires more than just good code—it requires strategic positioning, deep discovery, and the ability to handle complex technical objections.
- You are open to a hybrid work model and can work from our NYC office at least three days per week.
What You'll Do
- You help scale the impact of the Solutions function by creating reusable collateral, establishing solution patterns, and mentoring others on customer engagement and technical strategy.
- You discover and translate customer's strategic priorities and problem statements into high impact Agentic AI use cases leveraging Taktile during the sales process and throughout the Enterprise sales cycle, focusing on uncovering high-value AI use cases that justify significant investment and strategic partnership.
- You lead the design and execution of proof-of-value projects that combine customer data, ML/AI models, and Taktile’s platform to demonstrate strategic ROI. You build technical prototypes and demos leveraging the Taktile platform that simulate production-grade integrations and workflows.
- You collaborate with partners and customers to design and build solutions in Taktile's Agentic Decisioning Platform.
- You lead proof-of-value projects and can communicate the value opportunity of a full implementation and the corresponding strategic roadmap to senior stakeholders up to C-level executives.
- You work with product management to share competitive intelligence and prospect insights gathered during the sales process, helping shape Taktile's AI product roadmap and positioning strategy.
- You lead the discovery for new use cases and implement them on the platform to assess product-solution fit. You provide feedback to our product team and share results of your discovery with go to market functions.
Ideal, But Not Required
- You have experience operating in a technical leadership role—whether by owning strategic accounts, mentoring junior team members, or shaping solution strategy at scale in a high-growth environment.
- Live for Customer Value: You have at least 5-7 years of experience working within Enterprise Solution/ Sales Engineering in B2B SaaS, or in a senior technical consulting role
- Technical expertise: You have deep expertise with enterprise-level infrastructure and architecture, including an extensive understanding of APIs.
- You have experience building, tuning, or deploying ML models (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow) in production settings
- Experience with AI use cases in financial services (e.g. fraud detection, credit scoring, underwriting) is a strong plus.
- You are comfortable explaining how a model works to both a technical stakeholder such as a CTO and domain experts such as Credit Risk Managers
- You have acquired domain expertise in the financial services industry (banking, insurance, capital markets, payments, etc.).
Our Offer
- Work with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields. If you are similarly capable, caring, and driven, you'll find yourself at home here
- Make an impact and meaningfully shape an early-stage company
- Experience a truly flat hierarchy and communicate directly with founding team members. Having an opinion and voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo
- Learn from experienced mentors and achieve tremendous personal and professional growth. Get to know and leverage our network of leading tech investors and advisors around the globe.
- Receive a top-of-market equity and cash compensation package
- Get access to a self-development budget you can use to e.g. attend conferences, buy books or take classes.
- Use the equipment of your choice including meaningful home office set-up.
Our Stance
- We're eager to meet talented and driven candidates regardless of whether they tick all the boxes. We're looking for someone who will add to our culture, not just fit within it. We strongly encourage individuals from groups traditionally underestimated and underrepresented in tech to apply
- We seek to actively recognize and combat racism, sexism, ableism and ageism. We embrace and support all gender identities and expressions, and celebrate love in its many forms. We won't inquire about how you identify or if you've experienced discrimination, but if you want to tell your story, we are all ears
About Us
Taktile enables financial institutions to transform into AI-native organizations that are increasingly powered by autonomous agents. With our modular Agentic Decision Platform, customers combine AI agents, rules, relevant context, and human oversight to safely automate and optimize their decisions—approving more customers, reimbursing claims instantly, stopping fraud before it spreads, and financing every business worth funding. Founded in 2020, Taktile powers millions of decisions daily for institutions including Mercury, Monzo, Faire, and Pleo. With offices in New York, Berlin, London, São Paulo, and Iași, the company has raised $184M from Growth Equity at Goldman Sachs Alternatives, Index Ventures, Tiger Global, Balderton Capital, and Y Combinator. Learn more at taktile.com https://taktile.com.
About Your Employment. Taktile operates through regional entities worldwide. Depending on the location of this role, your employment or engagement will be with Taktile LLC (US), Taktile GmbH (Germany), Taktile Ltd (UK), or Taktile SRL (Romania). The applicable entity will be confirmed during the offer process.
Your Privacy. Taktile ("we" or "us") is the controller of the personal data you provide during this application process. We collect and process your name, contact details, resume/CV, work history, education, and any other information you submit or that we obtain from publicly available sources or references.
How we use your data: We process your personal data to evaluate your candidacy, communicate with you about the recruitment process, comply with legal obligations (such as right-to-work verification), and, with your consent, to consider you for future opportunities.
Legal basis (EU/UK applicants): We rely on (i) pre-contractual steps at your request (GDPR/UK GDPR Art. 6(1)(b)), (ii) legal obligations (Art. 6(1)(c)), and (iii) our legitimate interest in evaluating candidates (Art. 6(1)(f)).
Retention: If your application is unsuccessful, we retain your data for 12 months after the recruitment process concludes, unless you consent to longer retention. Successful candidates' data becomes part of their employment records.
Your rights: Depending on your location, you may have the right to access, correct, delete, or restrict the processing of your personal data, to data portability, and to withdraw consent. California residents have additional rights under the CCPA, including the right to know, delete, and correct personal information.
Automated decision-making: We use automated tools to assist in screening applications. No hiring decision is made solely by automated means without human review.
International transfers: Your data may be transferred to and processed in the United States, Germany, the United Kingdom, or Romania. Where required, transfers are protected by Standard Contractual Clauses or other approved mechanisms.
By submitting your application, you acknowledge that you have read and understood Taktile's Applicant Privacy Policy https://taktile.com/legal/applicant-privacy-policy. To exercise your rights or ask questions, contact privacy@taktile.com.
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: Hamburg
adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually.
Architecting Intelligence to Optimize 200M+ Daily Decisions
As the intelligence core of our engineering organization, our Data Science team doesn't just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time.
Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren't just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange.
Engineered for performance, our stack leverages Tensorflow and PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem.
The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second. As a Data Engineer on this team – you'll be building and maintaining the infrastructure that makes them possible: the Feature Store, the data pipelines, the data quality systems, and the data architecture that data scientists depend on to move fast.
Your Mission & Who We Are Looking For:
- Data engineering at ML scale. You have 5+ years in data engineering on a modern stack, with proven experience handling systems that process several TB of data per day and thousands of events per second.
- Flink is your default for real-time. You have hands-on experience with Apache Flink for stateful stream processing and real-time feature computation. You'll translate Data Science requirements into high-performance streams, enable Data Scientists to contribute new features and implement features yourself when needed..
- Pipeline bottlenecks don't survive long around you. You know how to identify and eliminate inefficiencies in complex ETL jobs, whether handling high-volume batch processing or real-time streaming systems like Kafka. At adjoe, data velocity is critical: slow pipelines directly impact model freshness and prediction quality at sub-100ms inference.
- You think in layers, not tables. You move beyond raw data to design robust, multi-layered data architectures using dbt, and can reason confidently about storage formats, Data Lakehouse models, and what belongs where in a 1PB+ data lake. Familiarity with Medallion Architecture is a strong plus.
- The bridge between Data Science and Backend. You've worked closely with Data Scientists on online ML systems with low latency requirements, and understand what it takes to make experimental research production-ready. Strong Java required; Go or Python a plus.
- Owns quality, not just delivery. You implement data validation, monitoring, and governance processes in production, because in a system where model inputs directly drive advertiser ROI, data integrity isn't optional. Experience with Airflow, Kubeflow, AWS, Terraform, and Kubernetes is a strong plus.
🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.
What’s in It for You?
At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day.
- Go Big. Own projects with impact on 770M users and push adtech boundaries.
- Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.
- Be Direct. Solve problems openly and collaborate across teams.
- Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.
- Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.
We welcome applications from people who will contribute to the diversity of our company.
Задачи:
— анализ банковских и крипто-транзакций для выявления мошенничества и AML-сценариев
— разработка и улучшение ML-моделей для fraud detection
— graph analysis / Graph ML (GNN, node embeddings, link prediction)
— вывод моделей в production
Требования:
— опыт работы с transactional fraud / AML от 5 лет
— strong Python + ML stack (PyTorch / TensorFlow)
— опыт с Graph ML / Neo4j / NetworkX / GNN
— production ML и ETL pipelines
Будет плюсом:
— MLOps
— ClickHouse / Elasticsearch / Cassandra
— опыт с real-time systems и асинхронным Python
Условия:
— релокация (Узбекистан / Дубай / ЕС) или B2B outside РФ/РБ/Украины
— зарплата в валюте
— relocation package
— международная русскоговорящая команда
— сложные ML/AI задачи и сильная technical culture
УдалённоseniorОАЭ, Узбекистан; SENIOR DATA SCIENTIST / ML ENGINEER | RELOCATION OR B2B REMOTE | #data #scientist #ml #engineer #relocation https://teletype.in/@courierus/e05v3dQsz7M; релокация (Узбекистан / Дубай / ЕС) или B2B outside РФ/РБ/Украины Известная международная IT-компания в сфере кибербезопасности ищет Senior Data Scientist / ML Engineer в команду Anti-Fraud; Условия: релокация (Узбекистан / Дубай / ЕС) или B2B outside РФ/РБ/Украины, зарплата в валюте, relocation package, международная русскоговорящая команда, сложные ML/AI задачи и сильная technical culture
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: 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: Bangalore, India
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 our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
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).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
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.
Location: Brussels, Belgium
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 our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
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).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
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.
Location: Abu Dhabi, United Arab Emirates
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 our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
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).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
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.
Location: Amsterdam, Netherlands
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 our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
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).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
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.
Location: Barcelona, Spain
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 our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
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).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
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.
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