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Location: New York, New York; New York City Metropolitan Area; New Jersey; Connecticut; San Francisco Bay Area, California Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name What You’ll Do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice What We Look For: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses) Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production IaC depth: AWS CDK, CloudFormation, Terraform Open-source contributions or public writing on applied AI What We Offer: Full-time employment On-site visits to clients’ facilities and our office in NYC 1/week Unlimited Vacation policy Generous health, vision, and dental insurance 401(K) matching plan Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data No Visa sponsorship How We Hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO

Location: New York; Massachusetts; Washington DC-Baltimore Area; Pennsylvania Workplace: remote About the role: We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name What You’ll Do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice What We Look For: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses) Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production IaC depth: AWS CDK, CloudFormation, Terraform Open-source contributions or public writing on applied AI What We Offer: Full-time employment On-site visits to clients’ facilities and our office in NYC 1/week Unlimited Vacation policy Generous health, vision, and dental insurance 401(K) matching plan Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data No Visa sponsorship How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO

Location: Tallinn, Estonia Are you looking for the next professional opportunity, that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Data Analyst to mainly c ollaborate with stakeholders and Product Owners/Analysts to understand their data needs and provide actionable insights based on data analysis. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Data Analyst will have the chance to: • Collaborate with stakeholders and Product Owners/Analysts to understand business requirements and support data-driven decision-making. • Analyze large and complex datasets to identify trends, patterns, and actionable insights. • Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to stakeholders. • Support the implementation of data-driven solutions that improve business performance and operational efficiency. • Contribute to analytics projects related to product performance, client behavior, acquisition funnels, and client lifecycle analysis. • Ensure data accuracy and consistency through validation and quality checks. • Work closely with BI team members to improve reporting processes and analytical capabilities. • Stay up to date with industry trends, analytical techniques, and data visualization best practices. What do you need to succeed in this role? • Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, Information Systems, or a related discipline. • Minimum 2–4 years of experience as a Data Analyst or in a similar analytical role, preferably within the Finance/FX industry. • Strong analytical and problem-solving skills with the ability to collect, organize, analyze, and interpret data accurately. • Excellent communication skills with the ability to present analytical findings to both technical and non-technical stakeholders. • Experience gathering business requirements and translating them into reporting and analytical solutions. • Experience performing cohort analysis, funnel analysis, segmentation, retention analysis, and KPI performance monitoring. • Hands-on experience with data visualization tools (Power BI preferred). • Strong SQL skills and understanding of dimensional modeling concepts, semantic models, and how to consume data from existing star schemas. • Working knowledge of DAX and Power BI data modelling principles. • Demonstrated ability to independently translate ambiguous business questions into structured analytical approaches and actionable recommendations. • Attention to detail, curiosity, and a proactive approach to solving business problems. • Excellent command of English, both written and spoken. • Strong teamwork and collaboration skills. Will be considered as a plus: • Experience with statistical analysis and A/B testing concepts. • Basic knowledge of machine learning concepts and their business applications. • Proficiency in Python or R for data analysis and automation. • Experience working with financial services, trading, or FX data. • Familiarity with data governance and data quality best practices. • Knowledge of Agile methodologies and DataOps principles. • Familiarity with Databricks or similar cloud platforms. • Experience conducting market, competitor, or benchmarking analysis. By joining us, you can expect: • A Unique Opportunity for a career in a global, fast-growing company. • Attractive remuneration package based on qualifications and experience. • Opportunities to learn and grow through our “ Employee Training & Development program”. • Stebby Sports Compensation or Confido Health Compensation. • Multiple events to bond with the team and the group. • Birthday and Loyalty benefits . What to expect from our recruitment process: Interview with HR Assessment task Interview with hiring managers Final interview with top management Make your next Career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Warsaw, Poland Are you looking for the next professional opportunity, that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Data Analyst to mainly c ollaborate with stakeholders and Product Owners/Analysts to understand their data needs and provide actionable insights based on data analysis. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Data Analyst will have the chance to: • Collaborate with stakeholders and Product Owners/Analysts to understand business requirements and support data-driven decision-making. • Analyze large and complex datasets to identify trends, patterns, and actionable insights. • Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to stakeholders. • Support the implementation of data-driven solutions that improve business performance and operational efficiency. • Contribute to analytics projects related to product performance, client behavior, acquisition funnels, and client lifecycle analysis. • Ensure data accuracy and consistency through validation and quality checks. • Work closely with BI team members to improve reporting processes and analytical capabilities. • Stay up to date with industry trends, analytical techniques, and data visualization best practices. What do you need to succeed in this role? • Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, Information Systems, or a related discipline. • Minimum 2–4 years of experience as a Data Analyst or in a similar analytical role, preferably within the Finance/FX industry. • Strong analytical and problem-solving skills with the ability to collect, organize, analyze, and interpret data accurately. • Excellent communication skills with the ability to present analytical findings to both technical and non-technical stakeholders. • Experience gathering business requirements and translating them into reporting and analytical solutions. • Experience performing cohort analysis, funnel analysis, segmentation, retention analysis, and KPI performance monitoring. • Hands-on experience with data visualization tools (Power BI preferred). • Strong SQL skills and understanding of dimensional modeling concepts, semantic models, and how to consume data from existing star schemas. • Working knowledge of DAX and Power BI data modelling principles. • Demonstrated ability to independently translate ambiguous business questions into structured analytical approaches and actionable recommendations. • Attention to detail, curiosity, and a proactive approach to solving business problems. • Excellent command of English, both written and spoken. • Strong teamwork and collaboration skills. Will be considered as a plus: • Experience with statistical analysis and A/B testing concepts. • Basic knowledge of machine learning concepts and their business applications. • Proficiency in Python or R for data analysis and automation. • Experience working with financial services, trading, or FX data. • Familiarity with data governance and data quality best practices. • Knowledge of Agile methodologies and DataOps principles. • Familiarity with Databricks or similar cloud platforms. • Experience conducting market, competitor, or benchmarking analysis. By joining us, you can expect: • A Unique Opportunity for a career in a global, fast-growing company. • Attractive remuneration package based on qualifications and experience. • Opportunities to learn and grow through our “ Employee Training & Development program”. • Hybrid Work Flexibility. • Multiple events to bond with the team and the group. • Birthday and Loyalty benefits . What to expect from our recruitment process: First interview with hiring managers or an HR call Psychometric test Final interview with top management Make your next Career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Limassol, Cyprus Are you looking for the next professional opportunity, that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Data Analyst to mainly c ollaborate with stakeholders and Product Owners/Analysts to understand their data needs and provide actionable insights based on data analysis. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Data Analyst will have the chance to: • Collaborate with stakeholders and Product Owners/Analysts to understand business requirements and support data-driven decision-making. • Analyze large and complex datasets to identify trends, patterns, and actionable insights. • Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to stakeholders. • Support the implementation of data-driven solutions that improve business performance and operational efficiency. • Contribute to analytics projects related to product performance, client behavior, acquisition funnels, and client lifecycle analysis. • Ensure data accuracy and consistency through validation and quality checks. • Work closely with BI team members to improve reporting processes and analytical capabilities. • Stay up to date with industry trends, analytical techniques, and data visualization best practices. What do you need to succeed in this role? • Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, Information Systems, or a related discipline. • Minimum 2–4 years of experience as a Data Analyst or in a similar analytical role, preferably within the Finance/FX industry. • Strong analytical and problem-solving skills with the ability to collect, organize, analyze, and interpret data accurately. • Excellent communication skills with the ability to present analytical findings to both technical and non-technical stakeholders. • Experience gathering business requirements and translating them into reporting and analytical solutions. • Experience performing cohort analysis, funnel analysis, segmentation, retention analysis, and KPI performance monitoring. • Hands-on experience with data visualization tools (Power BI preferred). • Strong SQL skills and understanding of dimensional modeling concepts, semantic models, and how to consume data from existing star schemas. • Working knowledge of DAX and Power BI data modelling principles. • Demonstrated ability to independently translate ambiguous business questions into structured analytical approaches and actionable recommendations. • Attention to detail, curiosity, and a proactive approach to solving business problems. • Excellent command of English, both written and spoken. • Strong teamwork and collaboration skills. Will be considered as a plus: • Experience with statistical analysis and A/B testing concepts. • Basic knowledge of machine learning concepts and their business applications. • Proficiency in Python or R for data analysis and automation. • Experience working with financial services, trading, or FX data. • Familiarity with data governance and data quality best practices. • Knowledge of Agile methodologies and DataOps principles. • Familiarity with Databricks or similar cloud platforms. • Experience conducting market, competitor, or benchmarking analysis. By joining us, you can expect: • Unique Opportunity for a career in a global, fast-growing company. • Attractive remuneration package based on qualifications and experience (including 13th salary and Discretionary  Bonuses to reward exceptional performance). • Opportunities to learn and grow through our “Employee Training & Development program”. • Medical Insurance Cover, which includes Outpatient, Inpatient, and Dental Care. • Multiple events to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company. • Participation in our welfare investment and savings plan through our Provident Fund Scheme. • Birthday and Loyalty benefits. • Collaboration with SportBenefit. What to expect from our recruitment process: First interview HR call Task Assessment Technical interview Final interview with top management Make your next Career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a VP of Research (Machine Learning) to define and lead the research direction behind its AI platform. This leadership role will shape how AI systems reason, learn, evaluate, and continuously improve within a product designed for high-frequency, real-world usage. Working closely with product and engineering leadership, this position will drive the long-term intelligence strategy, balancing cutting-edge research with practical production impact. Key Responsibilities Define and evolve the research roadmap for the platform's core AI intelligence, including context representation, memory, reasoning, planning, and orchestration. Evaluate and determine when to develop proprietary model architectures versus leveraging or adapting frontier open-source and commercial AI models. Design evaluation frameworks that measure real-world performance, robustness, safety, and long-term system behavior beyond traditional benchmark metrics. Lead the company's AI alignment, safety, and guardrail strategy as a core component of product development. Drive research and experimentation across advanced machine learning techniques, including: Retrieval-Augmented Training (RAG) Mixture of Experts (MoE) Model Distillation Multi-Agent Orchestration Multimodal AI Systems Partner closely with product and engineering teams to define and execute the intelligence strategy for AI-powered applications. Establish and maintain high standards for research quality, technical judgment, and engineering excellence across the organization. Requirements Extensive experience designing, building, and deploying machine learning systems in production environments. Strong technical expertise in model behavior, failure analysis, system evaluation, and long-term AI performance. Proven ability to translate advanced research into reliable, production-ready AI solutions. Demonstrated experience making high-impact technical decisions in fast-moving and ambiguous environments. Deep understanding of AI evaluation methodologies, model robustness, safety, and system reliability. Strong ownership mindset with the ability to lead technical strategy and execution. Passion for building practical AI systems that deliver measurable real-world impact rather than focusing solely on academic research or benchmark performance. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Technical Lead, Machine Learning to lead the execution of its AI platform by translating research into scalable, production-ready machine learning systems. This role sits at the intersection of research, infrastructure, and product, with responsibility for ensuring models are trainable, deployable, observable, and optimized for real-world performance. Working closely with research, engineering, and product teams, this position will drive the development of robust ML infrastructure while balancing performance, reliability, latency, and cost. Key Responsibilities Lead the end-to-end execution of machine learning systems, including data pipelines, training workflows, evaluation frameworks, inference architecture, and production deployment. Fine-tune and optimize models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation . Design, build, and operate scalable inference systems with a focus on latency, cost efficiency, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to measure model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU utilization, memory efficiency, inference optimization, and scaling strategies. Partner closely with application engineering teams to integrate machine learning systems into backend, desktop, and mobile products. Continuously improve production systems through rapid iteration, monitoring, and data-driven optimization. Requirements Proven experience building and deploying production-grade machine learning systems used by real users. Strong expertise working with large language models and understanding model behavior, limitations, and failure modes. Experience developing scalable ML infrastructure, training pipelines, and inference systems. Strong software engineering skills with the ability to write maintainable, production-quality code. Experience balancing real-world production constraints, including latency, reliability, scalability, cost, and safety. Strong ownership mindset with the ability to independently drive technical initiatives from design through deployment. Excellent communication and collaboration skills, with experience working in cross-functional, high-performing engineering teams. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Senior Machine Learning Engineer to design and build production-grade machine learning systems that power its AI platform. This is a hands-on technical role focused on solving complex machine learning challenges, translating research into scalable solutions, and delivering reliable AI systems that operate effectively in real-world environments. Working closely with research, product, and engineering teams, this position will independently own critical machine learning components from development through production deployment. Key Responsibilities Build and develop core machine learning systems that power AI-driven product capabilities. Own the end-to-end machine learning lifecycle, including data preparation, model training, evaluation, inference, deployment, and continuous iteration. Translate research concepts into reliable, production-ready machine learning solutions. Investigate and resolve model performance issues and production system failures using real-world operational insights. Continuously improve machine learning systems through rapid experimentation, measurement, and iteration. Collaborate closely with research, product, and engineering teams to deliver impactful AI features. Provide technical guidance through code reviews, best practices, and mentorship of fellow machine learning engineers. Develop solutions that balance real-world production requirements, including latency, scalability, cost efficiency, reliability, and safety. Requirements Proven experience building and deploying production machine learning systems used by real users. Strong understanding of modern machine learning models, including their behavior, limitations, and failure modes in production environments. Excellent software engineering skills with the ability to develop robust, maintainable, production-quality systems. Experience designing and implementing scalable machine learning pipelines and infrastructure. Strong ownership mindset with the ability to independently solve complex technical challenges from concept through deployment. Excellent problem-solving, communication, and collaboration skills within cross-functional engineering teams. Demonstrated ability to iterate quickly and continuously improve machine learning systems based on production feedback. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is looking for a Full Stack Engineer – AI Systems to build AI-native product experiences that transform advanced AI capabilities into intuitive, production-ready workflows. This role combines frontend, backend, and AI engineering to develop intelligent features that are reliable, scalable, and user-centric. Working closely with product, backend, and machine learning teams, this position will focus on designing end-to-end AI workflows, integrating large language models (LLMs), and delivering seamless user experiences across web applications. Key Responsibilities Build end-to-end product features across frontend, backend, and AI integrations. Design and develop AI agent workflows that support planning, tool usage, failure handling, and recovery across multiple steps. Integrate LLMs, memory systems, and external tools into scalable, production-grade applications. Design responsive AI interactions with streaming capabilities, partial results, and low-latency performance. Improve system reliability, observability, and fallback mechanisms for AI-powered features. Collaborate closely with product, backend, and machine learning teams to deliver features from concept to production. Continuously iterate and improve product functionality based on user feedback, production insights, and real-world usage. Requirements Strong experience in full stack software engineering across frontend and backend development. Solid understanding of system design, scalable architecture, and API development. Experience building AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or similar technologies. Ability to work effectively in fast-paced environments with evolving requirements. Strong ownership mindset with experience delivering features from ideation through production deployment. Excellent problem-solving skills and the ability to make pragmatic engineering decisions in ambiguous situations. Preferred Technical Skills Experience with some or all of the following technologies is preferred: Next.js Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a AI Backend Engineer to build and operate the backend infrastructure that powers AI-driven experiences across its products. The role focuses on owning the inference and orchestration layer that sits between AI models and end users, ensuring every interaction is fast, reliable, scalable, and cost-efficient. Working closely with engineering and AI teams, this position will play a key role in designing production-grade backend services, optimizing system performance, and delivering robust AI-powered features across mobile and desktop platforms. Key Responsibilities Build, maintain, and operate backend systems that power AI-enabled features in production. Design and implement AI inference pipelines, orchestration layers, and service architectures around AI models. Develop scalable, high-performance APIs that integrate seamlessly with frontend applications and machine learning systems. Optimize system performance by improving inference latency, throughput, caching, batching, and streaming capabilities. Own production operations, including monitoring, logging, alerting, and incident response. Troubleshoot and resolve issues within distributed systems to ensure service reliability and stability. Continuously improve backend architecture and production systems based on operational insights and real-world usage. Collaborate with cross-functional teams to deliver reliable, scalable, and high-quality AI-powered solutions. Requirements Strong backend engineering experience in production environments. Proven experience building and operating high-throughput, low-latency backend services. Experience designing scalable APIs and distributed systems. Familiarity with AI inference patterns, including Large Language Models (LLMs), embeddings, and multimodal AI systems. Strong debugging and troubleshooting skills within distributed production environments. Demonstrated ability to deliver production-ready solutions while iterating based on real-world system performance. Excellent analytical, problem-solving, and collaboration skills. Technical Skills Experience with the following technologies is preferred: Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Lagos, Nigeria Who We Are We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role The Senior Risk Analyst (Portfolio Risk) is responsible for driving portfolio risk analytics, credit performance monitoring, Expected Credit Loss (ECL) modeling, impairment analysis, and value-added risk initiatives that optimize portfolio performance and profitability. The role partners closely with Risk, Finance, Product, Collections, and Technology teams to deliver actionable portfolio insights, automate reporting, improve decision-making, and support strategic initiatives such as Risk-Based Pricing (RBP), digitalization, and portfolio optimization. This role is ideal for someone with strong analytical capabilities, deep knowledge of retail lending portfolios, IFRS 9/ECL methodologies, and the ability to translate complex data into business recommendations within a fast-paced financial services environment. What You Will Do Monitor and analyze portfolio performance across all lending products, identifying emerging risks, trends, and business opportunities. Develop, automate, and maintain portfolio risk dashboards, management reports, and executive reporting. Lead value-added portfolio initiatives including Risk-Based Pricing (RBP), digitalization, and portfolio optimization projects. Deliver timely, accurate, and insightful reporting to support strategic and operational decision-making. Own the portfolio Expected Credit Loss (ECL) and impairment analysis in accordance with IFRS 9 requirements. Provide profitability analysis by evaluating impairment costs, portfolio performance, and P&L contribution across each lending product. Support forecasting of credit losses, provisions, and portfolio performance under different economic scenarios. Design and enhance portfolio monitoring frameworks, early warning indicators, and risk performance metrics. Collaborate with Data, Finance, Product, Collections, and Technology teams to improve data quality and reporting automation. Build automated reporting solutions and improve data infrastructure to reduce manual processes. Conduct deep-dive analyses into portfolio trends, customer behavior, segmentation, and credit performance. Perform portfolio stress testing, sensitivity analysis, and scenario modeling. Support regulatory reporting, internal audits, and governance requirements relating to portfolio risk. Recommend risk policy enhancements based on portfolio performance and analytical findings. Maintain documentation for portfolio methodologies, reporting processes, and analytical models. Drive continuous improvement initiatives across portfolio analytics and reporting capabilities. Requirements What You Bring Educational Qualification Bachelor's degree in Statistics, Mathematics, Economics, Finance, Accounting, Computer Science, Engineering, or a related quantitative discipline. Master's degree is an added advantage. Professional Certifications FRM (Financial Risk Manager) – preferred. CFA (Chartered Financial Analyst) – an advantage. ACCA, ACA, or equivalent accounting qualification is beneficial. IFRS 9 or Credit Risk certifications are an added advantage. Microsoft Power BI, SQL, Python, SAS, or Data Analytics certifications are desirable. Experience Minimum of 5–7 years of experience in Portfolio Risk, Credit Risk Analytics, Risk Modelling, or Financial Risk. Experience within banking, fintech, consumer lending, digital lending, or financial services. Demonstrated experience with IFRS 9, Expected Credit Loss (ECL), impairment analysis, and portfolio monitoring. Experience building automated reporting and portfolio dashboards. Experience supporting senior management with portfolio performance insights and strategic recommendations. Professional Competencies Strong knowledge of portfolio risk management principles and retail lending products. Deep understanding of IFRS 9, ECL methodologies, impairment calculations, and provisioning. Strong analytical skills with experience interpreting large datasets and translating insights into business actions. Advanced proficiency in SQL, Excel, Power BI, Tableau, Python, SAS, R, or similar analytical tools. Strong understanding of P&L drivers, portfolio profitability, and financial performance analysis. Experience designing portfolio monitoring frameworks and early warning indicators. Ability to automate reporting processes and improve reporting efficiency. Strong knowledge of credit risk metrics including PAR, Roll Rates, Vintage Analysis, Loss Rates, Recoveries, and Collections performance. Excellent presentation, communication, and stakeholder management skills. Strong attention to detail with the ability to influence strategic decision-making through data. Ability to manage multiple priorities within a fast-paced environment. This Role Is Ideal For You If: You enjoy transforming complex portfolio data into strategic business insights. You are passionate about credit risk analytics, portfolio optimization, and automation. You enjoy improving reporting efficiency through digitalization and data-driven solutions. You thrive in solving complex business problems using analytics. You enjoy collaborating across Risk, Finance, Technology, and Product teams. You want to influence credit strategy and portfolio performance at scale. You May Not Enjoy This Role If: You prefer operational roles over analytical and strategic work. You are uncomfortable working with large datasets and complex financial models. You dislike automation, reporting, or continuous process improvement. You prefer highly repetitive work with limited opportunities for innovation. You are not interested in financial performance, impairment, or portfolio optimization. Benefits What's In It For You Opportunity to shape portfolio strategy within a leading fintech organization. Direct ownership of portfolio analytics, IFRS 9 reporting, and risk insights that influence executive decision-making. Exposure to large-scale digital transformation, Risk-Based Pricing (RBP), and advanced analytics initiatives. Opportunity to collaborate with Risk, Finance, Product, Data, Engineering, and Executive Leadership teams. Continuous learning, professional certification sponsorship, and career development opportunities. Competitive compensation and the opportunity to solve complex, high-impact credit risk challenges.

Location: Lagos, Nigeria Who We Are We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role The Senior Anti-Fraud & Credit Policy Manager leads the Bank's Credit Policy and Fraud Prevention function, ensuring robust controls across customer onboarding, loan origination, and portfolio management. The role is responsible for developing and optimizing fraud prevention strategies, KYC controls, credit policy rules, and fraud detection models while safeguarding the business against financial crime and operational losses. The successful candidate will oversee anti-fraud systems, external risk data providers, blacklist management, and continuous monitoring of fraud attacks. Working closely with Risk, Credit, Product, Operations, Technology, Compliance, and Data Science teams, this role will drive automation, enhance decisioning frameworks, and strengthen fraud prevention capabilities across the lending lifecycle. This role is ideal for someone with extensive experience in fraud risk management, credit policy, digital lending, and data-driven decisioning within banking or fintech. What You Will Do Lead the design, implementation, and continuous improvement of credit policies and anti-fraud strategies across all lending products. Develop, monitor, and optimize KYC, customer verification, and fraud prevention controls throughout the customer lifecycle. Design, implement, and fine-tune fraud detection rules, cross-match models, and decision engines to improve fraud detection while minimizing false positives. Manage fraud prevention platforms and decisioning systems to enhance approval quality and customer experience. Oversee relationships with external risk data providers, including credit bureaus, identity verification providers, device intelligence, and fraud intelligence vendors. Evaluate the effectiveness of third-party fraud and identity solutions and recommend enhancements where necessary. Own and maintain customer, device, identity, and merchant blacklists, ensuring timely updates and governance. Monitor fraud trends, emerging threats, attack patterns, and suspicious activities across digital channels. Lead daily fraud monitoring, investigate fraud incidents, and coordinate rapid response actions to mitigate losses. Develop fraud dashboards, KPIs, and management reports to support executive decision-making. Conduct root cause analysis of fraud events and implement preventive controls. Collaborate with Product, Engineering, Data Science, and Operations teams to implement new fraud controls and policy enhancements. Review lending policies and recommend updates based on portfolio performance, fraud trends, regulatory changes, and business strategy. Support internal and external audits, regulatory examinations, and compliance activities relating to fraud prevention and credit policy. Ensure all fraud prevention activities comply with regulatory requirements and internal governance standards. Lead continuous improvement initiatives through automation, analytics, and advanced fraud detection techniques. Requirements What You Bring Educational Qualification Bachelor's degree in Computer Science, Information Technology, Mathematics, Statistics, Economics, Finance, Accounting, Engineering, or a related discipline. Master's degree is an added advantage. Professional Certifications Certified Fraud Examiner (CFE) – preferred. Certified Anti-Money Laundering Specialist (CAMS) – an advantage. Certified Risk Management Professional (CRMP), FRM, or equivalent certifications are desirable. Professional certifications in Data Analytics, SQL, Python, SAS, or Power BI are an added advantage. Experience Minimum of 6–8 years of experience in Fraud Risk Management, Credit Policy, Financial Crime, Credit Risk, or Digital Lending. At least 3 years in a leadership or senior specialist role. Experience within banking, fintech, consumer lending, or financial services. Hands-on experience managing fraud prevention systems, KYC platforms, and rule-based decision engines. Experience working with external fraud intelligence, identity verification, and credit bureau providers. Professional Competencies Strong knowledge of digital fraud prevention, financial crime, and credit policy management. Deep understanding of KYC, Customer Due Diligence (CDD), identity verification, and fraud risk controls. Experience designing and optimizing fraud rules, scorecards, cross-match models, and decision engines. Strong understanding of fraud attack vectors, synthetic identity fraud, account takeover, device fraud, application fraud, and first-party fraud. Experience managing external risk data providers and integrating third-party fraud solutions. Strong knowledge of blacklist management, fraud monitoring, and fraud investigation processes. Proficiency in SQL, Excel, Power BI, Python, SAS, or similar analytical tools. Strong analytical and problem-solving skills with the ability to identify emerging fraud patterns. Excellent stakeholder management, communication, and leadership skills. Strong understanding of regulatory requirements relating to fraud prevention, AML, KYC, and consumer lending. Ability to balance fraud prevention with customer experience and business growth. This Role Is Ideal For You If: You enjoy building robust fraud prevention and credit policy frameworks. You are passionate about protecting customers and the business from financial crime. You enjoy analyzing fraud patterns and improving decision engines through data. You thrive in fast-paced, technology-driven lending environments. You enjoy collaborating across Risk, Compliance, Product, Engineering, and Operations teams. You are motivated by solving complex fraud challenges using analytics and technology. You May Not Enjoy This Role If: You prefer operational processing over strategic risk management. You are uncomfortable making high-impact risk decisions. You dislike working with fraud analytics, rule optimization, and large datasets. You prefer environments with limited change and innovation. You are not interested in regulatory compliance, fraud prevention, or credit governance. Benefits What's In It For You Opportunity to lead fraud prevention and credit policy for a fast-growing fintech organization. Ownership of fraud strategy, KYC controls, and credit decisioning frameworks that directly influence portfolio quality and customer trust. Exposure to advanced fraud technologies, digital identity solutions, and analytics-driven decisioning. Opportunity to collaborate with Risk, Product, Engineering, Data Science, Compliance, and Executive Leadership teams. Continuous learning, professional certification support, and career development opportunities. Competitive compensation and the opportunity to solve complex, high-impact fraud and credit risk challenges.

Location: Lagos, Nigeria Who We Are: We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role: The Portfolio Manager is responsible for developing, implementing, and managing credit portfolio strategies that support the Bank's expansion into new markets and regions. The role ensures sustainable portfolio growth by balancing risk, profitability, and customer acquisition while adapting credit strategies to local market dynamics and regulatory environments. This role will lead portfolio performance monitoring, market analysis, credit strategy optimization, and expansion initiatives across multiple geographies. Working closely with Credit Risk, Product, Finance, Data, Collections, and Business teams, the Portfolio Manager will drive data-driven decisions that maximize portfolio quality and business performance. This role is ideal for someone with strong expertise in portfolio management, retail lending, credit analytics, and expansion strategy within banking or fintech. What You Will Do: Develop and execute portfolio strategies to support expansion into new markets and regions. Design localized credit strategies based on customer behaviour, market conditions, regulatory requirements, and portfolio performance. Monitor portfolio quality, profitability, and growth across multiple regions using key credit risk metrics. Analyse portfolio trends, customer segments, and product performance to identify growth opportunities and emerging risks. Perform portfolio forecasting, scenario analysis, stress testing, and profitability assessments. Recommend enhancements to underwriting policies, pricing strategies, and portfolio limits to optimise business performance. Partner with Product and Business teams to support the launch of new lending products and market expansion initiatives. Monitor key portfolio indicators including delinquency, default rates, recoveries, vintage performance, roll rates, and loss trends. Conduct deep-dive analysis on regional portfolio performance and provide actionable recommendations to senior management. Collaborate with Finance on Expected Credit Loss (ECL), impairment analysis, and portfolio provisioning. Develop automated dashboards and portfolio reporting to support executive decision-making. Drive continuous improvement initiatives across portfolio analytics, reporting automation, and risk management processes. Ensure compliance with internal credit policies, regulatory requirements, and governance standards. Work closely with Risk, Data Science, Technology, Collections, and Operations teams to improve portfolio performance and customer outcomes. Requirements What You Bring Educational Qualification: Bachelor's degree or Higher National Diploma in Finance, Economics, Statistics, Mathematics, Business Administration, Engineering, Computer Science, or a related quantitative discipline. A Master's degree is an added advantage. Professional Certifications: Financial Risk Manager (FRM) or Chartered Financial Analyst (CFA) certification is preferred. Professional certifications in Credit Risk Management or Portfolio Management are an added advantage. Microsoft Power BI, SQL, Python, SAS, or equivalent data analytics certifications are desirable. Experience: Minimum of 5–7 years of experience in Portfolio Management, Credit Risk, Credit Analytics, or Retail Lending. Hands-on experience managing consumer lending portfolios within banking, fintech, or other financial institutions. Experience supporting regional expansion, multi-market portfolios, or new market launches is an added advantage. Professional Competencies: Strong understanding of retail lending, portfolio management, and credit risk principles. Experience analysing portfolio performance using key risk and financial metrics. Knowledge of IFRS 9, Expected Credit Loss (ECL), impairment analysis, and portfolio profitability. Strong analytical skills with experience using SQL, Excel, Power BI, Python, SAS, or similar analytical tools. Experience with portfolio segmentation, vintage analysis, roll rates, delinquency monitoring, and stress testing. Strong understanding of lending products, customer behaviour, and market dynamics. Excellent communication, stakeholder management, and presentation skills. Strong commercial acumen with the ability to balance business growth and portfolio quality. Ability to work effectively in a fast-paced, data-driven environment while managing multiple priorities. This Role Is Ideal For You If: You enjoy building and optimising lending portfolios across new markets. You are passionate about using data to drive strategic business decisions. You thrive in high-growth, fast-paced financial services environments. You enjoy collaborating with cross-functional teams to deliver business outcomes. You are motivated by solving complex portfolio and credit risk challenges. You May Not Enjoy This Role If: You prefer operational or administrative work over strategic portfolio management. You are uncomfortable working with large datasets and financial analysis. You dislike balancing commercial growth with risk management. You prefer highly repetitive work with limited opportunities for innovation and strategic thinking. Benefits What's In It For You: Opportunity to lead portfolio strategy for regional expansion within a fast-growing fintech organisation. Exposure to large-scale lending portfolios, market expansion, and strategic growth initiatives. Opportunity to collaborate with Credit Risk, Product, Finance, Data, Engineering, and Executive Leadership teams. Continuous learning, professional certifications, and career development opportunities. Competitive compensation and the opportunity to influence business growth while managing portfolio performance across multiple markets.

Location: Lagos, Nigeria Who We Are: We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role: The Credit Policy Analyst is responsible for designing, implementing, and continuously improving credit policies and underwriting strategies for new lending products, including Credit Cards, Credit Lines, Buy Now Pay Later (BNPL), Merchant Financing, and other emerging digital credit solutions. The role partners closely with Credit Risk, Product, Data Science, Fraud, Technology, Finance, and Operations teams to ensure new products are launched with robust credit decisioning frameworks that balance portfolio growth, customer experience, profitability, and risk management. This role is ideal for someone with strong expertise in credit policy development, consumer lending, and data-driven decision-making within a fast-paced banking or fintech environment. What You Will Do: Design and develop credit policies for new lending products, including Credit Cards, Credit Lines, BNPL, Merchant Financing, and other digital lending solutions. Define customer eligibility criteria, underwriting standards, credit limits, pricing strategies, and approval rules for new products. Develop, test, and optimize credit decision rules, scorecards, and policy frameworks to improve portfolio quality and customer acquisition. Monitor the performance of newly launched products and recommend policy enhancements based on portfolio analytics and business performance. Conduct policy simulations, scenario analysis, and impact assessments before implementing credit policy changes. Collaborate with Product, Data Science, Fraud, Engineering, Collections, and Finance teams throughout the product development lifecycle. Analyse customer behaviour, repayment trends, portfolio performance, and profitability to support policy improvements. Recommend changes to approval strategies, credit limits, pricing, and risk controls based on portfolio performance and market trends. Develop automated dashboards, portfolio monitoring reports, and policy performance metrics for management reporting. Support A/B testing and champion/challenger strategies to continuously improve credit decisioning. Ensure all credit policies comply with regulatory requirements, internal governance standards, and the Bank's risk appetite. Maintain comprehensive documentation of credit policies, governance approvals, decision rules, and implementation procedures. Support audits, regulatory reviews, and compliance activities relating to credit policy management. Requirements What You Bring Educational Qualification: Bachelor's degree or Higher National Diploma in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, Business Administration, or a related quantitative discipline. A Master's degree is an added advantage. Professional Certifications: Financial Risk Manager (FRM), Chartered Financial Analyst (CFA), or equivalent risk management certification is preferred. Credit Risk or Consumer Lending certifications are an added advantage. Professional certifications in SQL, Python, SAS, Power BI, or Data Analytics are desirable. Experience: Minimum of 4–6 years of experience in Credit Policy, Credit Risk, Portfolio Analytics, Consumer Lending, or Lending Strategy. Hands-on experience designing or managing credit policies for retail or digital lending products. Experience within banking, fintech, consumer finance, or other regulated financial institutions. Experience supporting the launch of new lending products is an added advantage. Professional Competencies: Strong understanding of consumer lending, underwriting principles, and credit policy management. Experience developing credit strategies for products such as Credit Cards, Credit Lines, BNPL, Merchant Financing, or unsecured lending products. Knowledge of scorecards, decision engines, credit bureau data, affordability assessments, and risk-based pricing. Strong analytical skills with experience using SQL, Excel, Power BI, Python, SAS, or similar analytical tools. Understanding of portfolio monitoring, IFRS 9, Expected Credit Loss (ECL), and portfolio performance metrics. Experience conducting policy performance analysis, segmentation, champion/challenger testing, and portfolio optimisation. Excellent analytical, communication, and stakeholder management skills. Strong attention to detail with the ability to balance business growth, customer experience, and credit risk. This Role Is Ideal For You If: You enjoy designing credit strategies for innovative lending products. You are passionate about balancing business growth with prudent risk management. You enjoy using data and analytics to improve customer decisioning. You thrive in collaborative, cross-functional product development environments. You enjoy solving complex lending and credit policy challenges. You May Not Enjoy This Role If: You prefer operational or administrative work over analytical and strategic roles. You are uncomfortable making data-driven credit policy recommendations. You dislike working with large datasets, policy optimisation, and performance analytics. You prefer highly repetitive work with limited opportunities for innovation. Benefits What's In It For You: Opportunity to shape the credit strategy for innovative lending products within a leading fintech organisation. Hands-on experience launching and optimising products such as Credit Cards, Credit Lines, BNPL, and Merchant Financing. Exposure to Product, Data Science, Risk, Engineering, Finance, and Executive Leadership teams. Continuous learning, professional certification support, and career development opportunities. Competitive compensation and the opportunity to solve complex, real-world lending and credit risk challenges.

Lokalise — сервис автоматизации перевода элементов UI в мобильных приложениях. Среди клиентов – Revolut, Starbucks, Mastercard и др. Требования: — 5+ лет опыта — Знание SQL, Python, DBT — Опыт работы с Metabase, Looker или Lightdash Информация о компании: — Размер команды – 200+ — Инвестиции – $56M Вакансия открыта для удалённой работы из Испании, Великобритании или Латвии.

Задачи: - Развивать бэкенд сбора и обработки данных: коннекторы к GitLab, Jira и другим системам, обогащение, агрегация и хранение данных, API для потребителей. - Превращать сырые данные из CI/CD и систем управления задачами в осмысленные метрики: разбираться, как реально устроены пайплайны, сборки и деплой в разных командах. - Решать задачи масштаба: надёжный сбор по сотням проектов, производительность, эволюция архитектуры под рост набора метрик и источников. - Развивать фронтенд (настройки проектов, дашборды): интерфейс относительно простой, но это полноценная часть продукта. Требования: - Опыт бэкенд‑разработки на Python от 4-х лет. - Понимание процессов разработки и доставки: CI/CD‑пайплайны, сборки, деплой. - Готовность к фуллстеку: фронтенд на TypeScript относительно простой, уверенное ориентирование в React‑коде. - Опыт с фронтендом будет плюсом, но не обязателен. - Интерес к данным: желание понимать, что стоит за цифрами, и докапываться до того, что именно они отражают.

Компания: Продуктовая IT-компания с офисом в Бостоне, США. Сервис помогает быстрее находить, оценивать и продвигать коммерческую недвижимость с помощью AI и глубокой аналитики рынка. Решение для брокеров, инвесторов и собственников, которым нужны актуальные листинги, точные инсайты и более быстрые решения по сделкам. Почему это интересно: — Продукт с реальной ценностью: Big Data + AI — Сильная команда инженеров и продуктовых специалистов — Минимум бюрократии, быстрые решения — Влияние на архитектуру и финальный продукт — Удаленная работа — Бонусы и stock options — Возможность релокации / стажировки в США — Время и ресурсы на рефакторинг и улучшения — Внутренние QA — разработчики не остаются один на один с качеством Задачи: — Разработка и развитие backend-компонентов продукта — Архитектурное проектирование и развитие серверной части системы — Руководство командой backend-разработки — Проведение code review, контроль качества кода и соблюдения инженерных стандартов — Участие в оценке задач, планировании спринтов и управлении техническим долгом — Проработка и внедрение решений по повышению производительности, стабильности и масштабируемости системы — Участие в проектировании и реализации новых функциональных модулей — Подготовка и актуализация технической документации — Взаимодействие с product-командой, дизайнерами и смежными техническими ролями — Наставничество разработчиков, участие в найме и онбординге — Внедрение и использование AI-агентов в продуктовых и внутренних процессах — Оценка, внедрение и масштабирование AI-решений — Обеспечение наблюдаемости, надёжности и управляемости AI-сервисов Требования: — Опыт в коммерческой разработке от 7 лет — Практическое использование AI агентов в процессах разработки от 1,5 лет — Опыт работы на каждом месте не менее 2,5 лет — Опыт управления командой от 3 лет — Английский не ниже В1 — Высшее техническое образование строго из списка ВУЗов: МФТИ, МГУ, НИУ ВШЭ, НИЯУ МИФИ, МГТУ имени Н. Э. Баумана, РУДН, МАИ, «МИСИС», ИТМО, СПбГУ, «ЛЭТИ», СПбПУ Петра Великого, УрФУ, Иннополис, ЮФУ, ТПУ, КФУ, НГУ, ТГУ, СФУ, Белорусский государственный университет, Белорусский национальный технический университет, Белорусский государственный технологический университет, БГУИР, КНУ им. Тараса Шевченко, КПИ им. Игоря Сикорского, ХПИ (Харьковский политех). Технологии: — PHP 8.x — MySQL / PostgreSQL — Redis — Elasticsearch — SQL — Linux — Git Будет преимуществом опыт работы с: — RabbitMQ — Go — Python — FastAPI — SQLAlchemy — Celery Условия: — График работы 5/2, оплачиваемый отпуск — Дистанционный формат работы из любой точки мира — Отсутствие бюрократии и микроменеджмента - ориентируются на результат

Задачи: — Разрабатывать ПО под ОС Linux — Участвовать в развитии архитектуры проекта Требования: — Опыт работы с C++ от 2-х лет — Разработка под ОС Linux от 3-х лет — Наличие внедренных проектов, опыт интеграции оборудования в ИС — Хорошие знания библиотек STL — Опыт работы с Qt/QML от 3 лет Будет плюсом: — Опыт работы с фискальными регистраторами и другим торговым оборудованием, POS системами (Point Of Sale - Точка продаж) — Знания Shell, Awk, Python Условия: — Оформление в аккредитованную ИТ-компанию — Конкурентоспособную заработную плату (обсуждается индивидуально) — ДМС со стоматологией и льготными условиями для членов семьи — Технику для работы — Работу в уютном офисе в центре Москвы (ст. м. Савеловская), в Краснодаре или удаленно из других городов РФ, также есть офисы в Санкт-Петербурге (ст. м. Балтийская) — Возможность реализовать свой опыт и потенциал в интересных и многоплановых проектах — Развитие – оплата обучения на курсах и участие в конференциях — Возможность проведения и участия в митапах, хакатонах — Наличие корпоративных скидок PRIMEZONE и программ лояльности от компании — Наличие корпоративной библиотеки курсов — Возможность рекомендовать компанию своим друзьям, участвуя в реферальной программе