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Location: Hamburg Workplace: Hybrid 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 the sub-millisecond decision engine that powers 200 million daily ad interactions   The Demand Core team and backend platform squads build the foundational infrastructure that determines which of our thousands of active advertising campaigns are relevant to a user the moment they open Playtime. At our scale, system latency is a business failure: downtime means advertisers stop spending, users stop earning rewards, and publisher revenue stalls. As a Staff Backend Developer, you will own the architectural integrity, reliability, and long-term evolution of the distributed systems that power these decisions 200 million times every day across multiple teams. Go microservices load the active ad campaign catalog into memory, evaluating 40+ targeting constraints and 30+ real-time signals like geo, fraud status, budget caps, to rank potential user performance in milliseconds. Beyond individual services, you will define architectural patterns across the entire ad interaction chain: high-throughput processing of clicks, views, MMP postbacks from Adjust and AppsFlyer, and reward-triggering in-app events. You will govern our hybrid messaging architecture using SNS/SQS and Kafka, standardize backend data patterns across DynamoDB, relational, and analytical data stores, and ensure our core ad scoring pipelines remain resilient under massive load.   Your Mission & Who We Are Looking For:   - Production Golang Systems & Architecture Mastery: You bring extensive backend development experience (7+ years, with deep production Go expertise in distributed environments). You will define service boundaries, concurrency models, and runtime optimizations for our +99% Go microservice architecture, scaling the platform reliably beyond hundreds of millions of monthly active users. - High-Throughput Event Streaming & Architecture Patterns: You have deep experience architecting and standardizing asynchronous microservice communication using event backbones like Kafka, SQS/SNS, and Kinesis. You will establish org-wide streaming standards, schema evolution, and CDC patterns to process billions of daily API events and aggregate them into our data lake for sub-second querying. - Large-Scale Data Architecture & Platform Optimization: You understand database internals, distributed storage trade-offs, and low-level web standards. You will standardize data patterns (sharding, replication, DR) across hundreds of terabytes in DynamoDB, MySQL, Druid, and Athena, while leading high-stakes, zero-downtime database migrations and deprecations. - Data Science & Algorithmic Integration at Scale: You quickly grasp complex technical topics, distributed systems trade-offs, and applied mathematics. You will partner with our Data Science team to architect the runtime infrastructure that serves predictive models and machine learning algorithms directly within our sub-millisecond real-time ad targeting engine. - Technical Leadership & Organizational Leverage: You communicate fluently and precisely in spoken and written English. You drive alignment across squads through RFCs and Architecture Decision Records (ADRs), define org-level SLIs/SLOs, sponsor major technical migrations, and mentor Senior engineers across an international engineering team. - Plus: Cloud Resilience & Tooling: Hands-on experience with continuous profiling (e.g., Pyroscope, goroutine dumps), chaos engineering drills, and infrastructure automation using Terraform, Kubernetes, or AWS cloud networking. ‌ 🌎 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 shaping the architectural foundation behind one of the most impactful platforms in adtech. The systems and patterns you design will reach hundreds of millions of users and power billions of decisions every day.   - Go Big. Own the technical direction and platform architecture with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, establish golden paths that unlock engineering speed, and keep momentum. - Be Direct. Solve complex architectural bottlenecks openly and drive alignment across cross-functional teams. - Thrive Together. Grow with and elevate a diverse, global team of engineers from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, solve hard computer science challenges, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

Location: Philippines We are seeking an experienced, analytical, and highly meticulous Virtual Senior Accounting Support Specialist to manage revenue reporting, Accounts Receivable (AR) tracking, invoicing, and provider payroll support for Perio Providers Group (PPG) , a growing periodontal healthcare organization supporting 41 doctors across Southern California. This is a specialized, high-level accounting support role requiring strong core accounting principles, advanced math skills (including percentage-based calculations), and expert-level Microsoft Excel proficiency (PivotTables, XLOOKUP/VLOOKUP, SUMIFS). Operating under established procedures, you will consolidate multi-provider production data, investigate financial discrepancies, and deliver accurate financial summaries without relying on traditional accounting software like QuickBooks. Working Environment & Core Schedule Role Title: Virtual Senior Accounting Support Specialist Organization: Perio Providers Group (PPG) — Supporting 41 Periodontal Doctors Status: Full-Time (40 Hours / Week) Schedule: Monday – Friday, 8:00 AM – 5:00 PM PST (Pacific Standard Time) Core Technology Stack: Microsoft Excel (Advanced) , Outlook, Google Voice, Practice Production Reporting Portals (No QuickBooks access utilized) Primary Scope: Multi-Provider Revenue Consolidation, AR & Invoicing, Production-Based Provider Payroll Audit Top 3 Daily Tasks Revenue Management & Month-End Reporting: Collect and consolidate complex daily/monthly production reports across 41 doctors and multiple office locations, auditing figures for discrepancies and maintaining detailed revenue tracking sheets. Invoicing & Accounts Receivable (AR) Support: Prepare detailed invoice data, review office adjustments, track invoice and payment statuses, flag unusual ledger items, and build comprehensive AR reports in Excel. Provider Payroll & Production Audit: Audit raw production data underlying provider compensation, maintain payroll tracking spreadsheets, verify percentage-based payout figures against production totals, and prep payroll batches for executive approval. Core Responsibilities Multi-Location Revenue Consolidation: Extract and aggregate production figures across 41 periodontal providers; audit report entries for accuracy, identify balance discrepancies, and maintain master revenue summary workbooks. Invoicing & Ledger Adjustment Audits: Compile line-item invoice data and supporting documentation; analyze office fee adjustments, refunds, and write-offs, flagging any out-of-policy items for management review. Production-Based Payroll Support: Reconcile doctor production reports against contract compensation structures, calculating complex percentage-based tiers and maintaining structured payroll verification schedules. Advanced Financial Analysis in Excel: Build, maintain, and audit complex financial workbooks using PivotTables, XLOOKUP/VLOOKUP, SUMIFS, and custom formulas to support month-end financial closes. Communication & Confidentiality: Maintain secure communication with internal teams via Outlook and Google Voice, following strict data governance, confidentiality, and accounting procedures. Requirements Accounting & Financial Background: Strong foundational understanding of accounting principles, GAAP standards, invoicing, AR, and financial reporting workflows. (Staff Accountant or Senior Accountant background strongly preferred). Advanced Excel Proficiency: High-level mastery of Microsoft Excel, including hands-on experience building and auditing PivotTables, XLOOKUP / VLOOKUP, and SUMIFS functions. (Candidates without advanced Excel mastery will not be considered). Advanced Mathematical Skills: Demonstrated strength in quantitative analysis, financial auditing, and calculating complex percentage-based compensation or revenue splits. Analytical Discrepancy Auditing: Proven ability to scrutinize large data sets, cross-reference multi-source reports, and spot minor financial discrepancies independently. Procedure Adherence & Independence: Ability to follow established accounting protocols precisely while managing strict monthly close deadlines with high autonomy. Communication & Confidentiality: Excellent written and verbal English communication skills with absolute discretion when handling confidential financial and payroll data. Remote Workspace: Private, quiet, HIPAA/financial-compliant home office equipped with a high-performance computer (PC/Mac), high-speed internet, backup power/internet solutions, and a headset. Preferred / Bonus Qualifications Experience in Dental, Healthcare, or Medical Group accounting practices. Multi-location or multi-provider financial tracking experience (supporting 20+ providers). Experience auditing production-based or commission-based doctor/provider compensation. Ideal Candidate Profile You are a sharp accounting professional who lives in Microsoft Excel. You enjoy diving into complex production data, cross-checking percentage calculations down to the cent, and maintaining bulletproof AR, revenue, and payroll tracking spreadsheets for a multi-provider healthcare group.

Location: India; Australia; Japan; Singapore; Philippines; New Zealand About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.

Location: Islamabad, Pakistan Workplace: hybrid Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer , who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential. Key Responsibilities Develop, deploy, and maintain machine learning models and systems Conduct in-depth data analysis, preparation, and processing Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing Follow established security guidelines and identify potential risks Collaborate with peers to review and ensure designs are effective, flexible, and reusable Solve issues and provide feedback for engineering design and delivery processes Ensure that features are deployed according to requirements and operate without unintended side effects Create and maintain comprehensive documentation for models and processes Monitor and support deployed solutions to ensure they meet performance expectations Actively seek out information and internal solutions to ensure reusability and adoption of common technologies Our expectations 3+ years of experience in the Field. Previous software engineering experience is preferrable Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data). Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics. Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle. Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes. The ability to design solutions using common design patterns and various design tools. Experience in experiment design and the ability to validate the credibility of information from various sources. A solid understanding of the business value of delivered features. Strong problem-solving skills, with an emphasis on using technical facts and reasoning. Excellent communication and collaboration skills, including active listening and the ability to build consensus. A strong drive for continuous self-development and a collaborative mindset for contributing to communities. Ability to balance quality and speed depending on the case, and justify your decision Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers English communication skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer , who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential. Key Responsibilities Develop, deploy, and maintain machine learning models and systems Conduct in-depth data analysis, preparation, and processing Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing Follow established security guidelines and identify potential risks Collaborate with peers to review and ensure designs are effective, flexible, and reusable Solve issues and provide feedback for engineering design and delivery processes Ensure that features are deployed according to requirements and operate without unintended side effects Create and maintain comprehensive documentation for models and processes Monitor and support deployed solutions to ensure they meet performance expectations Actively seek out information and internal solutions to ensure reusability and adoption of common technologies Our expectations 3+ years of experience in the Field. Previous software engineering experience is preferrable Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data). Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics. Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle. Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes. The ability to design solutions using common design patterns and various design tools. Experience in experiment design and the ability to validate the credibility of information from various sources. A solid understanding of the business value of delivered features. Strong problem-solving skills, with an emphasis on using technical facts and reasoning. Excellent communication and collaboration skills, including active listening and the ability to build consensus. A strong drive for continuous self-development and a collaborative mindset for contributing to communities. Ability to balance quality and speed depending on the case, and justify your decision Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers English communication skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Mexico City, Mexico Workplace: hybrid As a highly-regarded high-tech unicorn company, we have been making a positive global impact since 2013. Harnessing the power of innovative mobile technologies, our core product is redefining ride-hailing, while simultaneously introducing new business verticals that are propelling us toward becoming a super app. With our cutting-edge solutions and dynamic work environment, we provide a unique opportunity for individuals to contribute to our mission of combating injustice on a global scale. You will play a pivotal role in managing and expanding our Intercity business line across 13 countries in Latin America, overseeing the operations in current cities, launching new geographies and new products, and driving our key metrics improvements. You will also be engaged in various cross-functional projects affecting the Intercity business in all of our countries across the globe Please notice that CVs in English will be considered primarily. Key Responsibilities Grow our Intercity vertical across 13 countries in LATAM macro region, initiate activities and projects to reach our main business KPIs; Monitor our business metrics and improve them by launching and executing different initiatives to acquire/retain both passengers and drivers; Participate in strategy development based on market & competitors analysis for Mexico, LATAM and for the whole Intercity vertical globally Generate & validate product, marketing or operational hypothesis through A/B test to improve our product Manage cross-functional projects with other teams: Product, Analytics, Marketing, Driver’s Acquisition, Ride-hailing, Customer support etc. Conduct regular quantitative marketplace & product metrics analysis to discover inefficiencies and identify growth opportunities Launch surveys and conduct phone and field interviews with our passengers and drivers Skills, Knowledge & Expertise Bachelor's degree and/or Master's Degree in Economics/ Econometrics/ Engineering/ Mathematics/ Statistics/Business/Management 2+ years of experience in the mobility /ride-hailing/ B2B & B2C delivery, e-commerce marketplaces in a data-heavy role (business/product/marketing/ops analyst), ideally with B2C products Enjoy working with numbers and applying a data-driven approach to problem-solving Have practical work experience with analytical tools such as SQL and Excel Have experience with hypotheses generation and testing them via MVP solutions Fluent English speaker and native Spanish speaker. Ready and know how to conduct custdevs, generate and check hypotheses (we love field work and speaking with our passengers and drivers); Ready for business trips in Mexico and abroad Job Benefits Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid The AI Solution Delivery team is expanding its capabilities in NLP to build production-grade AI products. We are looking for a Senior Data Scientist to architect, build and deploy complex models for automating customer support operations. You will be responsible for selecting the right technical approaches and ensuring the scalability of our solutions. A proven track record in applying advanced NLP techniques to real-world problems is required. Key Responsibilities Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance Translate complex business goals into well defined data science problems and quantifiable metrics Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance Support the development and growth of other team members through mentorship and participation in onboarding programs Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact Communicate complex technical concepts and findings clearly and concisely to both technical and non technical stakeholders Skills, Knowledge and Expertise 5 years of professional experience in a data science or machine learning role with deep focus on NLP. Previous software engineering experience is preferrable. An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus Expert level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit learn). Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields. Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment. Proven experience with event systems, deployment environments, and maintaining production services. Familiarity with technologies for streaming, batch, and async data processing. Strong understanding of software system design principles and the ability to contribute to architectural discussions. Experience in experimental design to validate hypotheses and measure the effectiveness of solutions. A solid grasp of security, risk, and control concepts in a production environment. Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer , who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential. Key Responsibilities Develop, deploy, and maintain machine learning models and systems Conduct in-depth data analysis, preparation, and processing Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing Follow established security guidelines and identify potential risks Collaborate with peers to review and ensure designs are effective, flexible, and reusable Solve issues and provide feedback for engineering design and delivery processes Ensure that features are deployed according to requirements and operate without unintended side effects Create and maintain comprehensive documentation for models and processes Monitor and support deployed solutions to ensure they meet performance expectations Actively seek out information and internal solutions to ensure reusability and adoption of common technologies Our expectations 3+ years of experience in the Field. Previous software engineering experience is preferrable Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data). Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics. Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle. Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes. The ability to design solutions using common design patterns and various design tools. Experience in experiment design and the ability to validate the credibility of information from various sources. A solid understanding of the business value of delivered features. Strong problem-solving skills, with an emphasis on using technical facts and reasoning. Excellent communication and collaboration skills, including active listening and the ability to build consensus. A strong drive for continuous self-development and a collaborative mindset for contributing to communities. Ability to balance quality and speed depending on the case, and justify your decision Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers English communication skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid You will lead analytics for our Intercity vertical — a core business driving long-distance travel across cities. This includes car-based rides as well as partner transportation networks such as buses and other regional operators. Your mission is to uncover opportunities for growth, optimize pricing and demand-supply balance, and help shape the future of intercity mobility for millions of users. You will manage a team that partners closely with product, operations, and marketing to improve unit economics, drive market expansion, and deliver a seamless experience for both passengers and drivers. From building forecasting models and demand-planning tools to analyzing new market entry strategies and measuring the impact of promotional initiatives, your work will directly influence business-critical decisions. In this role, you will act as a trusted advisor to product and business stakeholders — aligning analytics with strategic priorities, driving data-informed decisions, and creating scalable processes for the fast-growing Intercity vertical. Key Responsibilities Lead, mentor, and develop the analytics team, supporting performance, growth, and professional development Define and drive the analytics strategy, roadmap, and standards aligned with business and product objectives Oversee key metrics, experimentation, and analytical outputs to ensure quality, consistency, and impact Partner with product, engineering, and business leaders to embed data-driven decision-making across the organization Establish and continuously improve analytics processes, documentation, and governance Ensure data quality, integrity, and effective cross-team data collaboration Skills, Knowledge and Expertise 5+ years of experience in data analytics or data science 2+ years of people management, leadings of 5+ people Analytical mindset: structured and critical thinking, the ability to find a balance between the resources spent and the effect on the business Strong mathematical background with an emphasis on mathematical statistics, optimization theory, time series and causal inference Proficiency in Python and data analysis libraries Proficiency in SQL: ability to work with large amounts of data, write and optimize complex queries, create analytical data marts Experience in creating BI reports: Plotly / Redash / Tableau English: Professional Working Proficiency Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Annapolis Junction, MD, United States Job Title Senior‑Level Systems Engineer Why IDS? IDS believes in resolving conflict, building innovative approaches to do so. Combining operational expertise with an intimate understanding of today’s greatest challenges, we bring our customers the solutions required for success in a complex and multidimensional world. IDS tailors solutions for a diverse range of government, military, nonprofit, and public‑sector clients. Locations Annapolis Junction, MD Shifts Available Please note, candidates must be flexible. Shift times are general hours; some projects may require earlier or later reporting based on customer requirements. Job Description IDS is seeking a Senior‑Level Systems Engineer to support the definition and implementation of system architecture for an Agent Knowledge Management System utilizing an agentic framework for automated knowledge extraction. The engineer will work closely with project leadership to manage system integration, deployment strategy, compliance, testing, validation, and lifecycle sustainment. Key Duties • Collaborate with project leadership to manage system integration efforts across multiple components and teams • Develop, maintain, and execute deployment strategies and processes to ensure smooth product delivery • Coordinate technical efforts across engineering, data science, and UX teams to support integrated delivery • Ensure compliance with system standards and best practices through testing, validation, and lifecycle sustainment • Decompose project requirements into actionable technical tasks and specifications • Develop and maintain technical plans, milestones, and support code review activities • Maintain system architecture, integration, and deployment documentation • Conduct security, performance, and quality audits to ensure compliance Requirements • Bachelor’s degree with nine (9) years of relevant experience, or Master’s degree with seven (7) years, or Doctoral degree with five (5) years • Degree in Engineering, Physics, Astronomy, or a related technical field (e.g., Computer Science, Mathematics) • Experience designing and sustaining engineering systems across the full system lifecycle • Experience decomposing requirements and supporting system integration efforts • Familiarity with Agile development and CI/CD practices • Active TS/SCI with Polygraph Compensation • Salary range: $150,000 – $170,000 • Benefits

Location: Annapolis Junction, MD, United States Job Title Senior‑Level AI Engineer (Python) Why IDS? IDS believes in resolving conflict, building innovative approaches to do so. Combining operational expertise with an intimate understanding of today’s greatest challenges, we bring our customers the solutions required for success in a complex and multidimensional world. IDS tailors' solutions for a diverse range of government, military, nonprofit, and public‑sector clients. Locations Annapolis Junction, MD Shifts Available Please note, candidates must be flexible. Shift times are general hours; some projects may require earlier or later reporting based on customer requirements. Job Description IDS is seeking a Senior‑Level AI Engineer to support the AI and Emerging Technologies mission. The engineer will work closely with mission stakeholders to capture requirements, support structured planning, improve certification processes using AI/ML tooling, and develop AI‑enabled capabilities including fine‑tuning Large Language Models to enhance vulnerability identification and mitigation. Key Duties • Collaborate with technical leadership to design, develop, and maintain LLM orchestration frameworks • Integrate static analyzers, retrieval‑augmented generation (RAG) systems, and automated testing pipelines • Clean, transform, and vectorize documentation, source code, and test artifacts for LLM consumption • Design and implement database solutions to support RAG architectures, artifact storage, and audit trails • Work with systems engineers to architect and deploy networked AI tools within secure enclaves • Perform performance profiling, optimization, and scalability analysis of mission systems • Support security assessments and Authority to Operate (ATO) processes Requirements • Bachelor’s degree with eight (8) years of relevant experience, or Master’s degree with six (6) years, or Doctoral degree with four (4) years • Associate’s degree with ten (10) years of clearly related experience may be considered • Degree in Computer Science or a related field with substantial coursework in algorithms, data structures, programming languages, computer architecture, logic, and advanced mathematics • Proficiency in Python and AI/ML integration • Experience with LLMs, static analyzers, RAG frameworks, and relational and vector databases • Familiarity with Agile methodologies and tools such as Git, Jira, and Confluence • Relevant experience across the software development lifecycle • Active TS/SCI with Polygraph Compensation • Salary range: $155,000 – $175,000 • Benefits

Location: Annapolis Junction, MD, United States Job Title Mid‑Level AI Engineer (Python) Why IDS? IDS believes in resolving conflict, building innovative approaches to do so. Combining operational expertise with an intimate understanding of today’s greatest challenges, we bring our customers the solutions required for success in a complex and multidimensional world. IDS tailors solutions for a diverse range of government, military, nonprofit, and public‑sector clients. Locations Annapolis Junction, MD Shifts Available Please note, candidates must be flexible. Shift times are general hours; some projects may require earlier or later reporting based on customer requirements. Job Description IDS is seeking a Mid‑Level AI Engineer to support the AI and Emerging Technologies mission. The engineer will work closely with mission stakeholders to capture requirements, support structured planning, improve certification processes using AI/ML tooling, and develop AI‑enabled capabilities including fine‑tuning Large Language Models to enhance vulnerability identification and mitigation. Key Duties • Collaborate with technical leadership to design, develop, and maintain LLM orchestration frameworks • Integrate static analyzers, retrieval‑augmented generation (RAG) systems, and automated testing pipelines • Clean, transform, and vectorize documentation, source code, and test artifacts for LLM consumption • Design and implement database solutions supporting RAG architectures, artifact storage, and audit trails • Work with systems engineers to architect and deploy networked AI tools within secure enclaves • Perform performance profiling, optimization, and scalability analysis of mission systems • Support security assessments and Authority to Operate (ATO) activities Requirements • Bachelor’s degree with five (5) years of relevant experience, or Master’s degree with three (3) years, or Doctoral degree with no required experience • Associate’s degree with seven (7) years of clearly related experience may be considered • Degree in Computer Science or a related field with substantial coursework in algorithms, data structures, programming languages, computer architecture, and mathematics • Proficiency in Python and AI/ML integration • Experience with LLMs, static analyzers, RAG frameworks, and relational or vector databases • Familiarity with Agile development and tools such as Git, Jira, and Confluence • Relevant experience across the software development lifecycle • Active TS/SCI with Polygraph Compensation • Salary range: $105,000 – $125,000 • Benefits

Location: Gurugram, Haryana, India NEOLYTIX Management Trainee, RCM Revenue Cycle Management  |  Full-Time Opportunity  |  Gurugram DEPARTMENT Revenue Cycle Management LOCATION Gurugram (Onsite) SHIFT US Shift (5:00 PM–2:00 AM IST) ⚠  US Shift: This role operates on a US-aligned schedule, 5:00 PM to 2:00 AM IST, 5 days a week, onsite at our Gurugram office. Please apply only if you can fully commit to this schedule. ⚠  Eligibility Gate: Open to 2025 and 2026 graduates. Candidates who completed graduation in 2024 may apply and will be considered on a case-by-case basis, subject to approval. Candidates currently pursuing their degree or who graduated before 2024 are not eligible. The 6-Month Learning Journey Joining Neolytix as a Management Trainee, RCM is a full-time opportunity that begins with a structured 6-month learning journey. You are not thrown on the floor from day one. You will be trained, assessed, and made ready for live operations before you independently handle client work. Every stage of the journey is designed to build your skills progressively. Phase 1 Classroom Training 8 to 12 Days (Max 14) Structured instructor-led sessions covering US healthcare, medical billing, coding basics, and RCM workflows. Your LOB is decided within the first 2 to 3 days based on your performance, knowledge check, and operations team input. Phase 2 Operations Readiness Training 8 to 12 Days You move to the floor alongside senior team members and trainers. You apply classroom learning in a supervised, live operations environment with ongoing assessments. Phase 3 Production Ramp-Up 4 Weeks You begin handling real client work under close supervision. Accuracy, speed, and process adherence are tracked. Performance here determines your readiness to go live independently. Phase 4 Go Live Full Production You are cleared for independent production on your assigned LOB. This marks your transition from trainee to fully operational team member. Throughout the 6 months, there will be several assessments to evaluate your skill development. Your training path and LOB may be refined based on these assessment outcomes. Career Path Neolytix promotes from within. Here is where this journey takes you: Management Trainee Associate 1 Associate 2 Senior Associate 1 QA / SME About the Role Neolytix is a US-headquartered healthcare managed services organization serving 270+ provider organizations across the United States. We are building our next generation of RCM professionals through this full-time opportunity and we are looking for fresh graduates who are motivated, disciplined, and ready to build a real career in US healthcare operations. Revenue Cycle Management is how US healthcare providers get paid for the services they deliver. As a Management Trainee, you will be assessed, trained, and placed into one of three core RCM functional areas based on your skills and performance during the first days of training. Your LOB is not a default assignment. It is matched to where you will thrive. The Three RCM Areas Charge Posting & Payment Posting Translating patient services into medical billing codes and submitting claims to insurers, plus recording and reconciling payments received. Requires speed, accuracy, and coding discipline. Accounts Receivable (AR) Following up on submitted claims, resolving denials, and ensuring payments are collected from insurance payers. Requires analytical thinking, persistence, and clear communication. Credentialing Enrolling healthcare providers with insurance payers so they can legally bill for services. Covers CAQH, PECOS, payer portals, expirables, and compliance. Requires strong process discipline and attention to deadlines. Your LOB assignment is made within the first 2 to 3 days of classroom training, based on your knowledge check scores and the evaluation of the operations team. Once assigned, your entire training is aligned to that LOB. Key Responsibilities Attend and complete all classroom training modules within the defined timeline, meeting assessment benchmarks at each stage. Commit to the LOB assigned to you and engage fully in the training path designed for that functional area. Apply classroom learning during operations readiness training under the supervision of senior team members and trainers. Meet accuracy and productivity benchmarks during the 4-week production ramp-up before going live independently. Support team leads and senior specialists in achieving client SLAs and compliance targets once on the floor. Continuously learn and adapt to US payer requirements, billing rules, and client-specific workflows. Demonstrate consistent progress through assessments to qualify for transition to Associate 1. What You Bring Must-Have Bachelor's degree in any discipline, fully completed. Candidates currently pursuing a degree or with an incomplete graduation are not eligible. Graduated in 2025 or 2026. Candidates from 2024 will be considered on an exceptional basis only. Minimum 70% aggregate in 12th grade (CBSE, ICSE, or equivalent board). Minimum 70% aggregate in graduation. Excellent spoken and written English. You will be trained on and operate in live US healthcare processes. Basic proficiency in MS Excel and MS Word. Full commitment to the US shift: 5:00 PM to 2:00 AM IST, onsite in Gurugram, 5 days a week. Preferred Schooling from Delhi NCR or Tier 1 or Tier 2 cosmopolitan cities. Science or Commerce with Mathematics background (B.Sc, BCA, BBA, B.Com, or similar). Any internship or prior exposure to US healthcare, medical billing, or BPO operations. Eligibility Criteria Education: Bachelor's degree, any discipline, fully completed. No exceptions for incomplete or in-progress degrees. Batch: 2025 and 2026 graduates are the primary eligible batch. 2024 graduates may be considered on an exceptional basis subject to thorough review and approval. Academic Scores: Minimum 70% aggregate in 12th grade (CBSE, ICSE, or equivalent) and minimum 70% in graduation. Communication: Excellent spoken and written English is mandatory. Communication below this standard will not progress past the assessment stage. Systems: Basic MS Excel and MS Word. Comfortable learning new billing and EHR software during training. Shift: 5:00 PM to 2:00 AM IST, onsite in Gurugram, 5 days a week. Non-negotiable. Notice Period: Immediate joiners strongly preferred. Performance Expectations During the Learning Journey Assessment pass rate: minimum passing threshold on every module assessment throughout classroom and OJT phases. Attendance: full attendance during all training phases is expected without exception. Assignment completion: all practice tasks and training exercises completed on time. Ramp-up accuracy: error rate within acceptable threshold during the 4-week production ramp-up. Production readiness: cleared for independent live work by end of the learning journey. Post Go Live Daily productivity: meet case or task targets for the assigned LOB consistently. Quality: accuracy rate maintained within client and internal benchmarks. SLA contribution: support team-level SLA compliance on assigned client accounts. Hiring Process Stage 1: Resume Screening. Verified against eligibility criteria: graduation year, degree completion, 70% score thresholds, and shift readiness. Stage 2: Pre-Hire Assessment. Aptitude, comprehension, and communication test conducted at the Gurugram office. Evaluates English proficiency, analytical basics, and role readiness. Stage 3: Technical Interview. Interview with the Training Department to assess learning ability, communication standard, and initial LOB suitability. Stage 4: Counseling Session. Shortlisted candidates attend a session with the Analytics and Operations team to fully understand the role, the learning journey, the shift, and career expectations before a final decision is made. Stage 5: Offer. Benefits & Perks Group Health Insurance: Medical insurance coverage. Complimentary Dinner: One meal provided during shift hours at the Gurugram office. Cab Facility: Two-way pick-up and drop for the night shift. Why Join Neolytix Structured Learning, Real Work 6 months of structured training before going live on client accounts, not tutorials, not simulations. You build real skills on real processes. Defined Career Ladder Management Trainee to Associate 1 to Associate 2 to Senior Associate to QA or SME. Your pace is driven by your performance. US Healthcare Exposure Work on live US client accounts from day one of going live. The domain experience you build here is globally relevant and career-defining. 270+ Provider Network Join a team serving over 270 US healthcare provider organizations across hospital systems, clinics, and specialty practices.

Location: Kuwait City, Kuwait Workplace: onsite About Tabby: Tabby is the GCC's leading shopping and payments platform, giving millions of people across Saudi Arabia and the UAE more control in the way they spend, save and earn. Headquartered in Riyadh, we've grown into one of the largest fintech companies to come out of the Arab world, working with +65,000 sellers, from global names like Apple, IKEA, Adidas and Shein to the region's leading retail groups. We're now building a local team on the ground in Kuwait, with a renewed presence in the market coming soon. This is a rare chance to join us at the start of a local launch, shaping how we show up for Kuwaiti shoppers and sellers from day one, backed by the scale, technology and track record we've built across the region. If you want to help us build something significant in Kuwait, backed by proven regional success, we want to hear from you. About the role: We are looking for a hands-on Senior Risk Manager to help build Tabby’s risk capabilities in Kuwait, with combined responsibility for enterprise and credit risk. As one of our first local hires, you will establish the governance, policies, risk appetite and reporting required for launch, while providing credit risk oversight as the portfolio grows. You will work closely with Kuwait leadership and Group Risk, as well as Product, Compliance, Finance and Operations, to ensure we scale responsibly and meet local regulatory expectations. Key Responsibilities Building and maintaining Tabby’s local risk management framework for Kuwait, covering enterprise and credit risk and aligning it with Group standards and applicable regulatory requirements. Developing the local risk strategy, risk appetite statement, policies, limits, governance forums and management reporting required for launch and ongoing operations by aligning with Group standard and adapted to local requirements Owning the enterprise risk process, including risk identification and assessment, the risk register, key risk indicators, emerging-risk reviews, residual risk positions and remediation tracking. Providing independent risk challenges on new products, partnerships, customer journeys, operating models and other material business initiatives. Leading local credit risk oversight across the customer lifecycle, including underwriting and eligibility rules, credit limits, affordability, collections outcomes and portfolio quality, focusing on local regulatory requirements. Partnering with Group Risk and Product teams to calibrate credit strategies for Kuwait and assess model, policy and limit changes. Establishing clear early-warning indicators, thresholds and reporting to support timely, data-informed risk decisions. Preparing risk assessments, reporting and recommendations for local leadership, risk committees, the Board and regulators, as applicable. Supporting licensing activities, regulatory submissions, examinations and information requests in partnership with Compliance, Legal and other control functions as well as acting as primary risk contact for Internal Audit Coordinating risk input into business continuity, outsourcing and third-party risk, operational incidents and control assessments. Promoting a practical risk culture and helping teams understand how risks should be identified, assessed, escalated and managed as well as ensuring material risks and control gaps are escalated and addressed at the right level. Helping shape the future Kuwait risk organisation and supporting hiring as the business scales. You should apply if You have strong risk management experience within banking, fintech, consumer lending, payments or another regulated financial-services environment. You bring meaningful hands-on experience across both enterprise risk and credit risk, rather than exposure limited to governance or oversight. You have built or materially improved risk frameworks, policies, risk appetite, governance structures, reporting and control processes. You understand consumer credit risk across underwriting, credit policy, portfolio monitoring, collections performance and loss drivers.. You understand enterprise risk disciplines including risk and control assessments, KRIs, incident and issue management, operational resilience, third-party risk and emerging risks. You understand the Kuwait regulatory environment; experience engaging with the Central Bank of Kuwait or another GCC financial-services regulator. You can operate independently in a new-market environment and are comfortable building the essentials yourself before a wider team is in place. You can balance strong governance with practical, proportionate execution and constructively challenge senior stakeholders when required. You communicate complex risk topics clearly and can prepare decision-ready materials for leadership, governance forums and regulators. You work effectively across Product, Data, Operations, Compliance, Finance, Legal and Internal Audit. You hold a bachelor’s degree in Finance, Economics, Risk Management, Business, Mathematics or a related field; FRM, PRM, CFA or a comparable qualification is an advantage. You are professionally fluent in English; Arabic is an advantage

Location: Remote - US Founded in 2012, Bugcrowd is the preemptive security platform that unifies exposure discovery and assessment, offensive testing, and intelligence shaped by AI and human insight to help organizations avoid, discover, and validate real-world risk. Bugcrowd helps security teams move faster by identifying the exposures that matter most so they can act first and stay ahead of attackers. By combining the power of humans and AI, teams can preempt attack paths and prevent breaches. Based in San Francisco and New Hampshire, Bugcrowd is supported by General Catalyst, Rally Ventures, Costanoa Ventures, and others. Visit www.bugcrowd.com . Job Summary The Bugcrowd RL and Reasoning Team focuses on pushing the boundaries of autonomous cybersecurity by building authentic, verifiable reinforcement learning environments for world-leading foundational AI companies. As a Reinforcement Learning Engineer specializing in Reinforcement Learning from Verifiable Rewards (RLVR), you will design and scale automated verification pipelines that transform real-world software vulnerabilities into deterministic reward functions. In this role, you will bridge the gap between low-level security analysis and modern LLM reasoning models, engineering environments where AI agents learn to discover, exploit, and remediate software vulnerabilities with mathematical certainty. Instead of relying on subjective human feedback, your work directly powers the rigorous, verifiable reward signals that teach next-generation frontier AI models how to master complex cybersecurity domain logic. You will work at the intersection of fuzzing, dynamic program analysis, system exploitation, and scalable ML infrastructure to shape the safety and offensive/defensive capabilities of future artificial intelligence. Essential Duties and Responsibilities Design, build, and deploy high-throughput RLVR (Reinforcement Learning from Verifiable Rewards) environments that evaluate LLM action sequences against deterministic execution outcomes. Develop automated test harnesses, sandboxes, and verification engines that convert complex vulnerability research (e.g., memory corruption, web security, logic bugs) into binary pass/fail reward signals. Integrate Bugcrowd’s Mayhem automated analysis platform and real-world vulnerability feeds into continuous, scalable RL environment generation pipelines. Architect safe, isolated, and highly reproducible execution environments (using Docker, BuildKit, or Nix) capable of running thousands of simultaneous agent-driven exploitation and patching trajectories. Collaborate directly with researchers at frontier AI labs including Anthropic, OpenAI, and Cohere to define standard benchmark formats, observation spaces, and verifiable evaluation metrics for cybersecurity tasks. Implement precise telemetry, ground-truth verification algorithms, and trajectory logging to analyze agent reasoning paths and prevent reward hacking or false positives. Build low-level instrumentation and debugging tools to monitor memory states, process executions, and network behaviors during agent interaction cycles. Optimize infrastructure performance and environment reset latency to support massive-scale parallel sampling and distributed RL training workflows. Benchmark and evaluate frontier AI model performance across diverse offensive and defensive security challenges, such as automated fuzzing, exploit payload generation, and patch validation. Education, Experience, Knowledge, Skills, and Abilities Understanding of RL training workflows used by modern LLM systems, specifically execution-based feedback or Reinforcement Learning from Verifiable Rewards (RLVR). Proficiency developing applications in Python and low-level systems programming in C, with Rust experience being a strong plus. Solid understanding of software vulnerabilities, binary exploitation, fuzzing methodologies, or program analysis. Experience with DevOps pipelines (e.g., GitHub Actions), reproducible builds (Docker, BuildKit, Nix), and comfort working with Linux systems and low-level debugging. Experience working with or building benchmark environments (e.g., CTFs, SWE-bench, security challenges, or execution sandboxes). Preferred Experience Experience designing custom reward functions, ground-truth verifiers, or automated grading engines for AI safety and reasoning models. Background in low-level program analysis tools, sanitizers (e.g., ASan/MSan), compiler instrumentation, or automated exploit generation tools. Proven track record of participating in or developing competitive cybersecurity benchmarks, CTFs, or open-source AI evaluation frameworks. Working Conditions and Physical Requirements The ideal candidate must be able to complete all physical requirements of the job with or without reasonable accommodation. Sitting and / or standing - Must be able to remain in a stationary position 50% of the time Carrying and / or lifting - Must be able to carry / move laptop as needed throughout the work day. Environment - remote, work-from-home 100% of the time. Pay Range Disclosure At Bugcrowd, we strive for fairness, equality and to create an environment that allows our people to perform at their very best. Our compensation philosophy is to foster a collaborative community that rewards, attracts and retains the best possible talent. The provided salary details are based on US national averages and we retain the flexibility to tailor to the needs of the business. The national estimate for the current base range for the position of $176,400 - $242,550. This position may also be eligible to participate in a discretionary bonus program or commission plan, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. Culture At Bugcrowd, we understand that diversity in the workplace is vital to a company’s success and growth. We strive to make sure that people are included and have a sense of being part of making Bugcrowd not only a great product but a great place to work. We regularly hear from both customers and researchers that Bugcrowd feels like a family, and we strive to maintain that internally as well. Our team consists of a broad range of people: musicians, adventure sports junkies, nature lovers, parents, cereal enthusiasts, night owls, cyclists, artists—you get the point. At Bugcrowd, we are solving security threats and vulnerabilities that are relevant to everyone, therefore we believe solving these problems takes all kinds of backgrounds. We value the perspectives and experiences people from underrepresented backgrounds bring. Disclaimer This position has access to highly confidential, sensitive information relating to the technologies of Bugcrowd. It is essential that the applicant possess the requisite integrity to maintain the information in the strictest confidence. The company is authorized to obtain background checks for employment purposes under state and federal law. Background checks will be conducted for positions that involve access to confidential or proprietary information (including trade secrets). Background checks may include Social Security verification, prior employment verification, personal and professional references, educational verification, and criminal history. Applicants with conviction histories will not be excluded from consideration to the extent required by law. Any personal data you submit in connection with your application will be processed in compliance with Bugcrowd's Privacy Policy, which you may review here: https://www.bugcrowd.com/privacy . Equal Employment Opportunity: Bugcrowd is EOE, Disability/Age Employer. Individuals seeking employment at Bugcrowd are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation. Bugcrowd is committed to the full inclusion of all qualified individuals. In keeping with our commitment, Bugcrowd will take the steps to assure that people with disabilities are provided reasonable accommodations. Accordingly, if reasonable accommodation is required to fully participate in the job application or interview process, to perform the essential functions of the position, and/or to receive all other benefits and privileges of employment, please contact HR at ADA at bugcrowd.com. Apply at: https://www.bugcrowd.com/about/careers/

Location: Remote - European Region Workplace: hybrid Coinspaid Solutions is a fintech company building blockchain payment infrastructure for the global economy. We design, implement, and scale payment systems that connect digital assets with real-world financial operations. Our solutions help businesses and financial institutions operate efficiently in the evolving digital asset landscape. For over 11 years, we’ve been developing products that bring crypto payments closer to mainstream adoption. Today, our team includes 350+ professionals working remotely across multiple countries. We combine the pace of fintech with a long-term approach to building products, teams, and careers. As a remote-first company, we give people flexibility in how they work while maintaining strong collaboration and shared ownership across teams. 🏆 In 2026, Coinspaid was recognized as Best Corporate Culture in the Blockchain Industry in Europe, reflecting our focus on ownership, trust, and collaboration. Responsibilities: Gathering, validating and documenting business and system requirements Modelling business processes, including crypto transaction flows and identifying opportunities for process improvements Identifying issues, risks and benefits of existing and proposed solutions, outlining business and technical impacts Designing and documenting integrations with external systems (blockchain networks, liquidity providers, payment systems) Creating functional and system specifications (PRD, SRS, API specifications, diagrams) Simplifying complex technical and blockchain-related concepts for cross-functional teams Defining business problems through in-depth investigation and gathering of technical and non-technical information Outlining detailed requirements and ensuring delivered solutions meet business needs Participating in integration testing, UAT, and validation of financial and transaction flows Improving and maintaining product and project documentation standards Participating in development of methods and techniques for requirements management and business case preparation Collaborating with engineering, product, and business teams on solution design Understanding of blockchain fundamentals (transactions, confirmations, fees, wallets) Knowledge of major blockchain networks (Bitcoin, Ethereum, EVM-based chains) Experience working with APIs (REST, WebSocket), webhooks and event-driven systems Understanding of end-to-end transaction lifecycle (deposit, processing, settlement, withdrawal) Experience with SQL and data analysis Ability to analyze logs, API responses and transaction data Familiarity with tools such as Postman, Swagger Requirements: 5+ years of experience as a Business/System Analyst Strong analytical, mathematical and problem-solving skills Strong communication and stakeholder management skills Ability to explain complex ideas in a simple and user-friendly way Effective logical thinking and structured approach High level of prioritization, focus, and self-motivation Good understanding of SDLC, PDLC, Agile methodologies Experience with business analysis tools and process modelling (BPMN, UML, etc.) English level: B2 (spoken and written) Why should you choose Coinspaid? You’ll be joining a company that is actively shaping its space – with enough scale to matter and enough room to make an impact. At Coinspaid, people are expected to think, contribute, and take ownership – and are supported in doing so. We focus on flexibility, wellbeing, and long-term growth – without overcomplicating how benefits work. Flexible Benefits Benefit Bar – up to €230/monthA flexible monthly budget you can use for what matters most to you – from sports and mental health to coworking, home office, or medical-related expenses. Work & Flexibility Fully remote work from almost anywhere Optional offices and relocation support Flexible, async-friendly environment Growth & Learning Budget for courses, certifications, and professional development Language learning support Cross-team learning and knowledge sharing Wellbeing & Support Medical insurance or reimbursement depending on location Access to mental health support Financial support for important life events Extras Merch shop with rewards system Team offsites and company events   Sounds good? Well then, we can’t wait to see your resume! To learn more please visit: https://coinspaid.com/about-us/ & https://coinspaid.com/careers/

Location: United States; Canada; Mexico; Costa Rica; Panama; Guatemala About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.

Location: Brazil; Argentina; Colombia; Chile; Peru; Uruguay About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.