About Us

Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.

Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Visit our institutional page https://international.nubank.com.br/careers/  

About the team

Portfolio Solutions is the team within Nu Asset Management responsible for the firm's ETFs and systematic fundos, and the allocation models behind our products and the broader Nubank ecosystem. We believe most of an investor's long-term return comes down to three things: cost, allocation, and discipline. Our job is to deliver all three at scale — which means we treat infrastructure, automation, and AI tooling as core to investment research, not as side projects.

We're looking for a quantitative analyst to strengthen our research, index construction, allocation modeling, and the platform that ties it all together.

What you'll do

• Research, design, and implement indices and systematic strategies across fixed income, equities, and derivatives — including structures such as covered calls, duration barbells, and factor portfolios
• Build and maintain multi-asset allocation models, with attention to efficient replication, tracking error control, and transaction costs
• Run rigorous backtests: no look-ahead, no survivorship, realistic costs. We don't publish a curve without out-of-sample replication
• Help build the quantitative infrastructure of the team: reusable data pipelines, backtest frameworks, monitoring dashboards, and reporting workflows on Databricks. The goal is that every model you build outlives the project it was born in
• Develop AI-powered tools for investment research: LLM-driven analysts on top of our internal datasets, agents for routine analytical tasks, copilots that compress the distance between question and answer for the whole team
• Support the launch of new ETFs — from index methodology to interactions with index prodviders, market makers, administrators, and custodians
• Read papers, replicate results, and tell apart what works from what looks like it works

What we're looking for

• Bachelor's degree in a quantitative field: engineering, math, physics, statistics, economics, computer science, quantitative finance, or equivalent
• 3+ years in quantitative research, systematic asset management, risk, or adjacent roles 
• Strong Python (pandas, numpy, scipy). Comfort writing code that other people will read, run, and extend
• Curiosity about — and ideally experience with — building production-grade analytical infrastructure: pipelines, jobs, dashboards, internal tools
• Genuine interest in applying LLMs and AI agents to quantitative work, not just as users but as builders
• Familiarity with the Brazilian market: NTN-B, IMA, Ibovespa, B3 derivatives, local ETF dynamics
• A collaborative, constructive way of working: you ask for help when stuck, you offer help when others are, you document, you review code, you disagree clearly without making it personal, and you give credit generously
• Ability to communicate quantitative results clearly — to portfolio managers, commercial teams, and ultimately to the end investor

Nice to have

• CFA, CAIA, FRM, or a graduate degree in a quantitative field
• Experience with ETFs, index replication, or benchmark construction
• Hands-on Databricks (Workflows, Delta, Unity Catalog, Databricks Apps), version control discipline, MLOps fundamentals
• Experience designing or shipping internal tools, copilots, or RAG systems

Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.
• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Observability: 5+ years of experience working with observability tools, and defining

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organizational & Communication Skills: Self-organized with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.
• Language: English proficiency is mandatory.

#LI-Remote

#LI-DC1

AE Studio is a development, data science, and design studio that works closely with founders and executives to create custom software and machine learning solutions.

We build products, platforms, and internal ventures that increase agency for all conscious beings. We combine world-class software engineering, AI expertise, and product design to ship ambitious projects that matter.

We’re looking for a Full-Stack Developer who bridges modern web engineering with practical AI; someone who can design, build, and ship production-ready, AI-powered applications while maintaining the standards of a top-tier software developer.

What You’ll Do

• Design and ship end-to-end applications from prototype to production across frontend, backend, and cloud.
• Build clean, scalable APIs and services and integrate AI models where they create real value.
• Create AI pipelines (data ingestion, preprocessing, embeddings, retrieval, orchestration) that are reliable and maintainable.
• Engineer prompting strategies and guardrails for real-world performance (latency, cost, accuracy), not just demo hype.
• Integrate AI features into full-stack apps with robust APIs, frontend UX, and CI/CD pipelines.
• Collaborate with designers, PMs, and engineers to deliver polished product experiences.
• Continuously evaluate new AI tools/models for performance, cost, and fit.
• Write production-grade, testable, maintainable code in TypeScript/JavaScript and Python (and other languages as needed).
  
  

What We’re Looking For

• 7+ years of professional software engineering experience.
• Proven track record shipping production applications (links to live products welcome).
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic), embeddings, vector databases, and orchestration frameworks.
• Strong command of modern web stacks (e.g., React/Next.js, Node.js/Nest/Fastify, Python/FastAPI) and cloud infrastructure.
• Solid grasp of architecture, scalability, performance, and security.
• A bias toward shipping with best practices (testing, code reviews, monitoring/observability).
• Clear communication, self-management, and comfort in a collaborative remote environment.
• Comfortable picking up new languages and frameworks, leveraging modern AI dev tools to move faster.
  
  

What Sets You Apart

• Experience fine-tuning models or training custom models on domain-specific data.
• Contributions to open-source AI or developer tooling.
• Mature approach to prompt engineering and evaluation (beyond trial-and-error).
• Background in data engineering or MLOps.
• Passion for AI alignment, agency-increasing technologies, and ethical AI development.
  
  

If you can write prompts that work today and code that still works in two years, we want to talk to you.

Salary range from $115k/year to $185k/year (if you're based in LA). Not in the range? That's fine, you can still apply and our team may fit you in a more senior position that we're not actively hiring for right now, since we are growing fast and may have other openings soon.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

The salary range for this role is $50,000 - $120,000 per year (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated  Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.

What You'll Do:

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
• Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

What We Look For:

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Preferred Qualifications:

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is $50,000 - $120,000 per year (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.

What You'll Do:

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
• Support Marketing Team’s AI Utilization with an eye on Cross-Departmental impact: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

What We Look For:

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Preferred Qualifications:

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The Mission

This is a senior role for someone who leads from both directions at once — deeply technical on customer engagements, and fully accountable for the growth and performance of a team of ML engineers and architects. You will report to the Director of AI/ML.

You own hiring, development, and team health alongside leading complex customer engagements, shaping architecture, and driving pre-sales. Both parts of this job are real and ongoing. The right candidate will find energy in that combination, not tension.

Your Assignment

Leading Your Team

• Hire and build: Set the technical bar for ML roles on your team, lead or oversee technical assessments, and make hiring decisions you can stand behind. Build a team that raises the practice's overall standard.
• Develop people: Run regular structured 1:1s, provide candid feedback at meaningful milestones, and actively invest in each person's growth — whether they are early in their career or highly experienced.
• Manage performance: Recognize strong contributors and address performance gaps directly and early. Partner with HRBPs and the Director of AI/ML when situations require a structured path, and advocate for your team when they deserve it.
• Stay close to staffing: Understand how your team is utilized across engagements, keep the staffing team informed of each person's skills evolution and preferences, and ensure people are placed in work that stretches them appropriately.

Strategic Advisory

• Lead ML assessments: Evaluate customer environments end-to-end — infrastructure, data pipelines, model lifecycle, and organizational readiness — and produce recommendations that drive executive decisions and open the door to the next engagement.
• Shape architecture: Serve as the senior technical authority on engagements, setting architectural direction, ensuring technical quality across the team, and making the calls that matter when tradeoffs are hard.
• Advise on ML operations: Help customers build ML systems they can actually own and sustain — translating MLOps, LLMOps, and production monitoring complexity into standards their engineering teams can execute and their leadership can act on.
• Drive pre-sales: Partner with sales and solutions teams during scoping and proposal phases, contributing the technical depth needed to scope work accurately and give prospects confidence in Caylent's ability to deliver.

Hands-On Delivery

• Lead engagements end-to-end: Drive architecture and solution design from kickoff through delivery — setting technical direction, unblocking the team on hard problems, and ensuring the work meets Caylent's quality standards.
• Own the technical relationship: Depending on the engagement, you are either the primary client contact owning all architect-level outcomes, or the senior technical authority providing oversight across the team. The expectation is the same in both cases — you are the person the engagement depends on technically.

Growing the Practice

• • Raise the bar internally: Mentor engineers and architects through real work, contribute to technical interviews, and build reference architectures and accelerators that make the broader ML practice better.

Your Qualifications (non-negotiables)

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Demonstrated people management experience — hiring, performance calibration, career development, and the ability to have difficult conversations directly and constructively.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether classical ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization, and distributed training — combined with RAG and agentic system design, including multi-agent architectures, MCP integration, and human-in-the-loop patterns on AWS.
• Proven ability to operate independently in complex, ambiguous customer environments — navigating competing priorities, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Fluency in AIOps patterns — designing agentic workflows for anomaly detection, automated root cause analysis, and remediation across observability platforms — and the ability to translate AI operations outcomes into measurable business value for customers.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

• ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI
• AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)
• Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts
• AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly
• Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue
• Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate
• Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama
• MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness
• LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation
• Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

Benefits

• 100% remote work
• Flexible Time Off
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture 

The Mission

We are seeking an exceptional Machine Learning Architect to join our growing Cloud Native Applications team. The right candidate is someone who has deep expertise in ML system design and is passionate about working with our customers, partners, and colleagues to drive innovation forward. Your mission will be to work alongside Caylent’s Engineers, Engineering Managers, and Project Managers to deliver AWS solutions across our diverse and forward-thinking customer base. You’ll work with the latest technologies and support customers looking to bring cutting-edge ideas to market.

Your Assignment

• You will be a mission control specialist, guiding Cayliens and Customers alike through Agile ceremonies like stand-ups, retrospectives, and more.
• You will translate customer requirements and into a workable backlog of tickets for engineers.
• Delegate tickets to a team of engineers in order to complete customer projects.
• Lead requirements gathering, backlog grooming, and architecture discussions.
• Apply your understanding of DevOps pipelines, including build automation, branching strategies, CI/CD, Infrastructure as Code, security, monitoring, logging, and alerting.
• Troubleshoot and resolve issues in customer dev, test, and production environments.
• Automate software testing at multiple levels (component, configuration item, subsystem, system) and monitor results.
• Write production quality code, including unit and integration tests. 
• Work with a team to deliver top-quality cloud native applications on AWS for customers.
• Clearly communicate and document your designs, processes, and procedures.
• You will demonstrate a passion to Stay Curious as you mentor peers, tackle new technologies, and learn from our word-class team of engineers.
• Coach and mentor less experienced teammates, coach and be mentored by world class engineers.

Your Qualifications

Core Consulting Qualifications 

Customer Experience 

• Confidently addresses client questions and identifies gaps in requirements with  proposed next steps. 
• Focus on delivering clear, actionable solutions that meet client goals

Collaboration 

• Facilitates alignment across stakeholders or technical priorities and deliverables.
• Navigates differing perspectives with professionalism to ensure shared understanding  and progress. 

Communication 

• Breaks down complex technical concepts for non-technical audiences in a clear, concise  manner. 
• Adapts communication style based on audience and context to improve clarity and decision-making. 

Technical Qualifications

• Experience with IaC tools (CloudFormation, CDK, Terraform).
• Expert level experience in Amazon SageMaker and ML libraries (TensorFlow, MXNet, PyTorch, Scikit-learn).
• Strong understanding of ML concepts: feature engineering, hyperparameter tuning, optimization strategies.
• Familiarity with MLOps tools (MLflow, Neptune, Comet).

Benefits 

• 100% remote work
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.

About Us

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

About the Role
AI Platform Team - The mission of the AI Platform team is bold: to democratize AI by empowering every Nubanker—not just Data Scientists—with safe, scalable, and accurate Machine Learning capabilities.

We are looking for a Manager who is passionate about creating solutions that push the boundaries of our current stack. You will help us move beyond basic DS work to abstract the complexities of the entire ML lifecycle—from training and deployment to serving and governance.

Why is this role open?
We are scaling. Currently, our structure has grown significantly, and to ensure the organization's health and the growth of our engineers, we are opening this position to lead a dedicated squad. You will take ownership of a team that manages the base infrastructure for the entire Data Science function at Nubank.

You'll be responsible for:
As the ML Manager for the AI Platform, you will combine technical leadership with people management. You will lead a squad of 11 Machine Learning Engineers (varying from Senior to Intern levels) and work closely with a Staff ML Engineer and a Product Manager.

• People Management: Foster a culture of feedback and growth. You will guide the development of your direct reports, conducting performance reviews and helping them navigate their careers.
• Strategic Roadmap: Translate high-level business goals into actionable technical roadmaps. You will discuss needs with stakeholders and define the "how" and "when."
• Architecture & Innovation: Explore architecture gaps and opportunities. You won't just maintain; you will challenge the team to explore complex features like scalable parallel processing and better UX for Data Scientists.
• Execution: Conduct initiatives with autonomy and diligence, ensuring we deliver value while maintaining high engineering standards.
  
  

Nubank already has well-established tools for basic Data Science work. Your challenge is to take us to the next level. You will push the frontiers of technology to handle massive scale, integrate with multiple complex systems, and democratize access to AI tools across the company.

What we are looking for
You don't need to be a hands-on coder 100% of the time, but you must have the technical depth to challenge the team and understand the ecosystem.

• Experience in Leadership: You have experience managing high-performing engineering teams, sharing feedback, and hiring/developing talent.
• Domain Expertise: Solid background in ML Engineering, AI, or Data Science, specifically with a focus on MLOps, Infrastructure, and Platform building.
• Tech Stack Familiarity: You are comfortable discussing and architecting systems involving Kubeflow, SageMaker, and Databricks.
• The "Builder" Mindset: You enjoy building software. You want autonomy to make decisions and explore edge technologies, similar to the engineering culture found in Big Tech

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

The Role

The Data Practice Director is a senior leadership role within Caylent's Cloud Data Engineering (CDE) practice, reporting directly to the Data Practice Leader. This person is responsible for operationalizing the practice strategy, leading a team of data professionals, and owning delivery excellence across a portfolio of client engagements. They are the connective tissue between strategic direction and day-to-day execution, ensuring the practice delivers consistent, high-quality outcomes while scaling to meet growth targets.

Your Assignment

Practice Operations and Delivery

• Own end-to-end delivery oversight for a portfolio of data engineering and analytics engagements, ensuring on-time, on-budget, and high-quality outcomes.
• Drive operational rigor across the practice including utilization management, staffing coordination, margin tracking, and engagement health reviews.
• Develop and enforce delivery standards, reusable frameworks, and best practices that enable consistent, scalable execution across the team.
• Serve as an escalation point for active engagements, helping resolve technical blockers, scope issues, and client concerns in partnership with delivery leads.
• Partner with the Practice Leader to translate the strategic roadmap into executable quarterly priorities and team-level OKRs.

Team Leadership and Development

• Directly lead and develop a team of data engineers, architects, and analytics professionals across the practice.
• Set clear performance expectations, conduct regular reviews, and provide ongoing coaching to build a high-performing, engaged team.
• Partner with recruiting and workforce planning to identify talent gaps, support hiring decisions, and onboard new team members effectively.
• Foster a culture of ownership, continuous learning, and technical excellence across a globally distributed team.
• Identify and develop emerging leaders within the practice, creating growth pathways aligned to practice needs.

Client Engagement

• Build trusted advisor relationships with key client stakeholders, acting as a senior point of contact for delivery and strategic guidance.
• Partner with the sales and GTM teams to support business development activities including scoping, proposal development, and technical solutioning for new and existing accounts.
• Identify and pursue expansion opportunities within active client engagements, surfacing new use cases and service offerings that align with client needs.
• Represent Caylent with credibility and professionalism in client-facing conversations at the director and VP level.

Practice Growth and Enablement

• Collaborate with the Practice Leader on go-to-market positioning, service offering development, and internal capability building.
• Contribute to thought leadership content including whitepapers, webinars, and conference presentations that elevate the practice's external profile.
• Stay current on trends in the modern data ecosystem and work with the team to incorporate relevant innovations into our delivery approach.
• Support the development of practice IP including accelerators, reference architectures, and reusable solution components.

Your Qualifications

Experience

• 12+ years of experience in professional services or consulting, with a strong focus on data engineering, analytics, or data platform delivery.
• Demonstrated success managing and growing a team of 20 or more data professionals in a services or consulting environment.
• Proven track record of delivering complex data projects on AWS, including data lake, lakehouse, streaming, and analytics workloads.
• Experience managing a portfolio of concurrent client engagements, balancing delivery quality with financial performance.
• Hands-on background in data architecture or engineering, with the ability to engage credibly with technical teams and client stakeholders alike.

Leadership

• Strong people management skills with demonstrated ability to develop talent, drive performance, and build team culture across geographies.
• Ability to operate effectively at multiple levels, from strategic planning conversations with the Practice Leader to hands-on engagement support with delivery teams.
• Comfortable navigating ambiguity and complexity in a fast-paced, high-growth consulting environment.
• Experience influencing senior client stakeholders (director, VP and C-level) in delivery and advisory contexts.

Technical Acumen

• Deep familiarity with the AWS data ecosystem including services such as Redshift, Glue, EMR, Kinesis, Lake Formation, and Athena.
• Working knowledge of adjacent platforms including Databricks and Snowflake, and their integration with AWS-native architectures.
• Broad understanding of data engineering fundamentals: ingestion patterns, transformation frameworks (e.g., Spark, dbt), data modeling, governance, and quality management.
• Familiarity with MLOps and data science workflows sufficient to support and position those capabilities in client conversations.

Education

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• Master's degree or MBA is a plus.

Certifications

• AWS Certified Data Analytics, AWS Certified Solutions Architect, or equivalent certifications are a plus.

Preferred Qualifications

• Execution-Oriented: Skilled at translating strategy into structured plans and holding teams accountable to outcomes.
• Client-First Mindset: Genuinely invested in client success and capable of building durable, trust-based relationships.
• Collaborative Partner: Works effectively across sales, delivery, and practice leadership functions without siloed thinking.
• Clear Communicator: Able to convey complex technical and business concepts to diverse audiences with clarity and confidence.
• Growth Driver: Passionate about building teams, capabilities, and client relationships that compound over time.

Benefits

• 100% remote work
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

The Mission

We are seeking an Engineering Manager for our Cloud Data Engineering Practice. The right candidate is someone who is technically strong, can manage a team of Architects and Engineers, oversee data delivery engagements and is passionate about working with our customers, partners and employees to drive the business forward.

Your Assignment

• Manage a team of 5 - 8 cloud engineers and architects
• Interface with clients and internal teams to propose technical improvements using your cloud and engineering knowledge
• Take on hands-on technical responsibilities, including technical tasks in sprints 
• Lead technical discussions with customers
• Handle code reviews and pull request management
• Manage task assignments within sprints
• Perform technical leadership activities like roadmap and vision checks, best practices implementation, and risk identification
• In-project mentoring (understand people on project & creation of growth opportunities) and sharing feedback for team members on the project
• Technical accountability on the delivery
• Kickoff new client engagements and act as a point of technical escalation
• Develop and review proposals and contracts and present these to clients
• Perform technical interviews for Architect and Engineer candidates
• Perform weekly 1:1s with your direct reports and guide their career development
•  

Your Qualifications

• Strong experience in AWS data landscape
• Expertise in at least two major areas of Cloud Data Engineering:
  • Relational database design, optimization and migration
  • Big data processing using Spark, Hadoop, EMR etc
  • Machine Learning and MLOps
  • Advanced analytics using time series forecasting, descriptive and inferential statistics
  • BI dashboards and visualizations
  • Data Governance and MDM
• Experience with most of these:
  • Infrastructure as Code tools
  • CI/CD pipelines
  • Application modernization and migration with a strong focus on databases
• Excellent written and verbal communication skills

Benefits

• 100% remote work
• Flexible Time Off
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Caylent is a place where everyone belongs.  We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.   

We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.

The Opportunity

This is a senior technical client leadership role that blends deep hands-on ML expertise with strategic advisory and consulting skills. You will be the most experienced ML voice across a diverse and expanding book of customer engagements — from early-stage companies bringing ambitious ML ideas to market, to established enterprises modernizing how they build and operate AI systems on AWS.

You will shape strategy, influence architecture, and leave every team you touch better than you found it. You bring the scientific depth to design and evaluate models rigorously, the engineering depth to architect production ML systems at scale, and the consulting instincts to translate both into business value for customers.

If you have led the hard conversations, shaped the architecture decisions that mattered, and built the things others benchmark against — and you are looking to do that across a growing portfolio of varied and interesting customers — this is the role for you.

What You'll Do

• Lead end-to-end ML assessments across infrastructure, data pipelines, model lifecycle, and organizational readiness — producing recommendations that drive executive decision-making and earn Caylent the next engagement.
• Partner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of work.
• Serve as the senior technical authority on client engagements — possibly across multiple projects simultaneously — providing architectural guidance, ensuring technical quality from your project team members, and getting hands-on when the engagement demands it, without owning day-to-day implementation responsibilities.
• Own or orchestrate high-quality POCs that give customers confidence before committing to a larger initiative.
• Advise customers on ML operations standards and architecture — covering MLOps pipeline design, model lifecycle management, LLMOps patterns, and production monitoring frameworks — translating operational complexity into decisions and guardrails their teams can own and sustain.
• Shape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customers.
• Strengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to accelerators, reference architectures, and thought leadership content.

What You Bring

The non-negotiables

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether traditional ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards and decisions that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization (quantization, vLLM), and distributed training (DeepSpeed, FSDP) — combined with RAG and agentic system design, including multi-agent architectures, event-driven workflows, MCP integration, and human-in-the-loop patterns on AWS. Technical authority to prescribe the right approach and set architectural standards that teams can execute against.
• Proven ability to operate independently in complex customer environments — navigating ambiguity, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Hands-on experience designing and deploying SRE agents and AI-driven operations workflows in production — spanning automated incident detection, triage, and remediation — with the ability to integrate across observability platforms and translate AI operations outcomes into measurable business value.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI

AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)

Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts

AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly

Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue

Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate

Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama

MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness

LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation

Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

Benefits

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers.  We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference.  You will develop solutions designed by an architect.

You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer.  Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.

Your Assignments

• Work with a team to deliver machine learning solutions on AWS for customers
• Participate in and contribute to daily standup meetings
• Develop and implement ML models, MLOps, and analytics
• Big data processing and preparation of training data for models

Your Qualifications

• Strong experience in building ML models for real world applications
• Strong experience in at least one of these:
• AWS ML Services/SageMaker
• ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
• MLOps tools such as MLflow, Kubeflow, Airflow
• Advanced analytics using time series forecasting and/or inferential statistics
• Strong experience in one or more of these data processing solutions:
• Big data processing platforms like Spark, Hadoop, or streaming platforms
• Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
• Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
• Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
• Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
• Excellent written and verbal communication skills

Benefits 

• 100% remote work
• Generous holidays and flexible PTO
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.

Somos o acelerador que impulsiona o crescimento na Ibero-América, combinando a excelência global em engenharia da EPAM com a experiência regional e a proximidade cultural da NEORIS. Ajudamos as organizações a escalar, modernizar e avançar em sua transformação digital por meio de soluções em Cloud, Data & Analytics, Inteligência Artificial, Cibersegurança, Automação Inteligente, Consultoria Estratégica e Engenharia de Software.

Respaldados por mais de 60.000 profissionais em mais de 55 países e por um sólido modelo Nearshore, conectamos capacidades globais com confiança local para gerar impacto real, crescimento sustentável e resultados de alto valor para nossos clientes.

Acreditamos que a diversidade impulsiona a inovação. Por isso, todas as nossas oportunidades estão abertas para todas as pessoas, independente de gênero, raça, idade, identidade, orientação ou condição. 

Oferecemos

• Vale Refeição e Vale Alimentação: Benefícios mensais para suas despesas com alimentação, dentro e fora de casa. 
• Previdência Privada: Planejamento de futuro com contribuição complementar à aposentadoria. 
• Plano de Saúde: Cobertura médica de alta qualidade para você e seu dependente legal. 
• Plano Odontológico: Cuidados odontológicos completos, com ampla rede de atendimento. 
• Seguro de Vida: Proteção e segurança para você e seus entes queridos. 
• Aulas de Inglês/Espanhol: Incentivo ao aprendizado de idiomas. 
• Wellhub: Benefícios e descontos em academias e programas de bem-estar. 
• Auxílio Creche: Suporte financeiro para despesas com educação infantil. 
• Neoris Global Campus: Plataforma de desenvolvimento com oportunidades contínuas de aprendizado e crescimento profissional. 
•  

Se você possui experiência e tem interesse em participar de iniciativas estratégicas, cadastre seu perfil em nosso banco de talentos.

Te convidamos a nos conhecer em http://www.neoris.com, Facebook, LinkedIn, Twitter e Instagram: @NEORIS.
#LI-KC1

Location: São Paulo (on-site) 

About us

AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.

About AB InBev Growth Group

Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world.

In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities. 

We are looking for Data Product Managers to join our Computer Vision team, playing a critical role at the intersection of business, data science, and engineering. You will own the strategy, execution, and adoption of AI-powered computer vision products used across global markets. 

This role requires strong product leadership, fluency in ML-driven products, and the ability to translate complex technical capabilities into business value for commercial and customer stakeholders. 

What you'll do:

Drive Strategic Alignment 

• Partner with global commercial stakeholders across LATAM, US, and Mexico to enable product understanding, drive adoption, and unlock new Computer Vision use cases.
• Act as a product evangelist—educating stakeholders on product capabilities, limitations, and roadmap.
• Provide regular updates to customers and internal stakeholders on product adoption, model performance, and business impact. 

 Plan & Prioritize 

• Own quarterly product planning in collaboration with Data Scientists, Data Analysts, Data Engineers, ML Engineers and software engineers.
• Balance business visibility, technical improvements, and infrastructure evolution when defining priorities.
• Continuously assess team capacity and delivery risk to ensure plans are realistic, achievable, and aligned with broader product and business strategy. 

Execute & Deliver 

• Partner closely with engineering and data teams to execute the quarterly backlog and deliver high-impact Computer Vision capabilities.
  
  
• Drive delivery of:
  New Computer Vision use cases
  Scalable and secure APIs
  State-of-the-art ML models
  Comprehensive BI visualization.  

• Define Epics and High-Level Requirements (HLRs), leading refinement sessions with a strong focus on:
  Dashboard visibility
  User experience (UX)
  Model behavior and performance 

• Lead Agile ceremonies, including daily stand-ups, sprint planning, reviews, and retrospectives. 
  
  
• Track delivery and performance metrics, producing sprint summary reports with emphasis on:
  Team productivity
  Model metrics
  Usage and adoption trends 

Engage Stakeholders 

• Maintain strong relationships with technical, commercial, and senior leadership stakeholders.
• Present quarterly roadmaps and progress updates with clarity and confidence.
• Proactively manage expectations by negotiating scope, timelines, and trade-offs across internal teams and customers. 

What you'll need:

• Proven experience managing data or ML-driven products, ideally within Data Science Products.
• Strong understanding of the ML lifecycle, including data preparation, training, deployment, monitoring, and iteration.
• Ability to translate business problems into technical product requirements for ML and AI solutions.
• Exceptional written and verbal communication skills, capable of bridging business, engineering, and data science audiences.
• Fluent English and Advanced Spanish to collaborate effectively with global teams.
• Willingness to work on-site in São Paulo

More about you:

• Solid background in Product Management or Data Product Management, preferably with ML/AI products.
• Hands-on experience writing Epics, High-Level Requirements (HLRs), and technical documentation—documentation is one of your strengths.
• Foundational understanding of software architecture, including databases, APIs, and ML models.
• Experience working in Agile environments with highly cross-functional teams (Data Science, ML Engineering, MLOps, Backend, Frontend).

What We Offer:

• Performance based bonus*
• Attendance Bonus* 
• Private pension plan
• Meal Allowance
• Casual office and dress code
• Days off*
• Health, dental, and life insurance
• Medicines discounts
• WellHub partnership
• Childcare subsidies
• Discounts on Ambev products*
• Clube Ben partnership
• Scholarship*
• School materials assurance
• Language and training platforms
• Transport allowance

*Rules applied

Equal Opportunity & Affirmative Action:

AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics.

The following fields are optional, but anticipate the information for your registration*.

Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. 

For more information: www.abinbev.com 

A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros e energia, somos apaixonados por ajudar nossos clientes, temos 40 escritórios nas Américas, Europa e Ásia-Pacífico! Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Como membro da equipe de Entrega de Tecnologia da Capco, você trará uma sólida base em ciência de dados aplicada, análise estatística e práticas ágeis de entrega. Como Cientista de Dados em IA Aplicada, você desempenhará um papel fundamental na transformação de dados complexos em insights acionáveis e soluções habilitadas por IA que apoiam resultados reais de negócio.

Você contribuirá ao longo de todo o ciclo de vida de analytics aplicado — desde análise exploratória e modelagem até validação e suporte em produção — trabalhando em estreita colaboração com engenheiros, equipes de produto e stakeholders. Seu trabalho ajudará a conectar técnicas analíticas avançadas com capacidades escaláveis e prontas para produção em projetos de alto impacto com clientes.

O que você fará:

• Realizar análises estatísticas, clusterização e modelagem probabilística para gerar insights e orientar soluções baseadas em IA
• Analisar dados estruturados em grafos para detectar anomalias, extrair padrões probabilísticos e apoiar inteligência baseada em grafos
• Construir pipelines de NLP com foco em NER (Reconhecimento de Entidades Nomeadas), resolução de entidades, extração de ontologias e scoring
• Contribuir para esforços de engenharia de IA/ML desenvolvendo, testando e implantando modelos e serviços orientados por dados
• Aplicar fundamentos de MLOps, incluindo rastreamento de experimentos, monitoramento de métricas e práticas de reprodutibilidade
• Colaborar com equipes multifuncionais para transformar análises em soluções prontas para produção
• Prototipar rapidamente, iterar com eficiência e ajudar a evoluir as melhores práticas de ciência de dados na equipe

O que você precisa ter:

• Experiência sólida em modelagem estatística, técnicas de clusterização e análise baseada em probabilidade
• Experiência prática com análise de dados em grafos, incluindo detecção de anomalias e extração de padrões de distribuição
• Fortes habilidades em NLP, com experiência em NER, extração de entidades/ontologias e métodos de avaliação relacionados
• Mentalidade voltada à engenharia, com capacidade de construir, implantar e otimizar soluções reais (não apenas teóricas)
• Conhecimento prático dos fundamentos de MLOps, incluindo rastreamento de experimentos e métricas de modelos
• Proficiência em Python e bibliotecas comuns de ciência de dados/IA
• Boa comunicação e capacidade de trabalhar de forma colaborativa em ambientes dinâmicos de IA aplicada
• Inglês avançado/fluente (será avaliado em entrevista) - Eliminatório.

.

POR QUE CAPCO:

Na Capco promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. 
Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade interna, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros. Nossas oportunidades são trabalhadas para todos(as)!
#LifeAtCapco

PRÓXIMOS PASSOS:

• Se você está ansioso(a) para progredir sua carreira conosco, candidate-se e aguarde o contato de um de nossos recrutadores!

Xometry is seeking a Senior Data Scientist to join our Generative AI team. The candidate will focus on training and fine-tuning Visual Language Models (VLMs) for multimodal document understanding. The ideal candidate will leverage their expertise in machine learning and computer vision to advance Xometry's capabilities in processing and extracting structured data from complex documents and images. This is a 1-year contract.  

Responsibilities:

• Develop, fine-tune, and evaluate Visual Language Models (VLMs) to enhance document understanding, focusing on multimodal data such as text, images, and technical drawings.
• Design and implement data preparation, cleaning, and augmentation processes tailored to multimodal model training, ensuring high-quality data pipelines for VLMs.
• Leverage transfer learning and pre-trained models to accelerate model development and optimize performance on Xometry’s specific data.
• Use cloud resources (e.g., Amazon Web Services) to scale training and fine-tuning processes for VLMs efficiently.
• Collaborate with data engineering and machine learning operations (MLOps) teams to deploy VLMs into production and monitor their performance.
• Interpret model outputs and improve model accuracy and robustness by applying data analysis and visualization tools (such as Python, Jupyter Notebooks, and SQL).
• Experiment with and implement state-of-the-art model architectures, continuously optimizing VLM performance in a fast-paced, iterative environment.
• Work within a team-oriented setting, participating in peer reviews, sharing insights, and contributing to an environment of continuous learning and improvement.

Qualifications:

• A bachelor’s degree is required; an advanced degree (M.S. or PhD) in computer science, data science, machine learning, or a related field is highly preferred.
• 5+ years of experience in data science and machine learning, with expertise in Visual Language Models or multimodal machine learning.
• Strong experience with machine learning libraries and frameworks such as PyTorch, TensorFlow, or Hugging Face.
• Proficiency in Python, including libraries like pandas, numpy, and scikit-learn.
• Solid understanding of deep learning techniques and experience with transfer learning, fine-tuning, and model evaluation.
• Experience with cloud platforms (e.g., AWS SageMaker) for model training and deployment.
• Familiarity with data processing and visualization tools (SQL, Jupyter Notebooks, Looker, etc.) and basic database knowledge (e.g., Snowflake, MongoDB).
• Excellent analytical and problem-solving skills, with a strong ability to work in an environment that values teamwork, innovation, and continuous learning.
• Familiarity with computer vision tasks and frameworks, as well as experience with multimodal data, is a plus.

#LI-Remote

A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros e energia, somos apaixonados por ajudar nossos clientes, temos 40 escritórios nas Américas, Europa e Ásia-Pacífico! Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Engenheiro de Inteligência Artificial

Responsabilidades:

• Projetar, desenvolver e aprimorar aplicações baseadas em foundation models (ex.: LLMs, modelos multimodais) para necessidades específicas de negócio;
• Implementar e experimentar técnicas de IA generativa, incluindo, mas não se limitando a, Retrieval-Augmented Generation (RAG) e prompt engineering;
• Liderar a implementação de agentes autônomos inteligentes e sistemas multiagente capazes de tomada de decisão complexa, execução de tarefas e interação com sistemas externos;
• Utilizar e contribuir para frameworks de IA agentic (ex.: LangChain, AutoGen, Semantic Kernel, Crew AI) para construir agentes robustos e escaláveis;
• Desenvolver e integrar soluções de Model Context Protocol (MCP) para padronizar como aplicações de IA acessam e utilizam fontes de dados externas, ferramentas e informações em tempo real;
• Liderar o desenvolvimento de aplicações full-stack que integrem modelos de IA generativa e sistemas agentic, garantindo experiências de usuário fluidas;
• Trabalhar com tecnologias de front-end (ex.: React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) e back-end (ex.: Python com Flask/Django/FastAPI, Node.js, Go);
• Projetar e implementar APIs RESTful escaláveis e microsserviços para expor funcionalidades de IA;
• Implantar, gerenciar e otimizar cargas de trabalho de IA/ML e aplicações full-stack em pelo menos uma grande plataforma de nuvem (AWS, Azure ou GCP);
• Implementar práticas de LLMOps/MLOps e DevOps para integração contínua, entrega contínua (CI/CD), implantação de modelos, monitoramento e gestão de ciclo de vida;
• Manter-se atualizado sobre os avanços mais recentes em IA generativa, sistemas agentic, foundation models e áreas relacionadas por meio de pesquisa e experimentação contínuas;
• Colaborar de forma eficaz com equipes multifuncionais, incluindo gerentes de produto, cientistas de dados, pesquisadores e outros engenheiros;
• Orientar engenheiros juniores, compartilhar conhecimento e promover uma cultura de excelência técnica.

Requisitos:

• Bacharelado ou Mestrado em Ciência da Computação, Inteligência Artificial, Machine Learning ou área quantitativa relacionada;
• 5+ anos de experiência em desenvolvimento de software com forte foco em IA/ML;
• Experiência comprovada na construção e implantação de modelos de IA generativa (ex.: LLMs, modelos de difusão) em ambientes de produção;
• Expertise demonstrada em projetar e implementar sistemas de IA agentic e arquiteturas multiagente;
• Sólido entendimento e experiência prática com Model Context Protocol (MCP) para integração de sistemas de IA;
• Experiência consistente em desenvolvimento de aplicações full-stack;
• Ampla experiência com plataformas de nuvem (AWS, Azure ou GCP) para implantações de IA/ML e hospedagem de aplicações em geral;
• Experiência com ferramentas e práticas de LLMOps (ex.: Langfuse, Langsmith, etc.);
• Excelentes habilidades de resolução de problemas, análise e comunicação;
• Capacidade de trabalhar de forma independente e colaborativa em um ambiente ágil e dinâmico;
• Inglês avançado.

Diferenciais:

• Experiência anterior com sistemas de conhecimento baseados em grafos.

• Familiaridade com ferramentas e frameworks de GenAI (LangChain, LlamaIndex, OpenAI APIs).

• Experiência em projetos do setor de seguros ou serviços financeiros.

POR QUE CAPCO:

Na Capco promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. 
Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade interna, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros.
Nossas oportunidades são trabalhadas para todos(as)!!!
#LifeAtCapco

PRÓXIMOS PASSOS:

• Se você está ansioso(a) para progredir sua carreira conosco, candidate-se e aguarde o contato de um de nossos recrutadores!

About Us

Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world’s largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia.

About the role

At AI Core, we are scaling the impact of our AI initiatives to become the primary driver of Nubank’s most critical decision systems. We are seeking an Lead Machine Learning Engineer (Applied AI Scientist) to lead high-impact research projects that bridge the gap between state-of-the-art AI and production-grade financial systems. You will be responsible for solving complex, ambiguous problems using Deep Learning and Foundation Models, ensuring our architectures are scalable, efficient, and driving measurable business results.

As an Applied AI Scientist (MLE), you’re expected to:

1. Research Execution & Technical Leadership (Complexity & Autonomy)

• Lead and execute complex applied research initiatives independently, focusing on building and optimizing architectures (e.g., Transformers, GNNs) that can be deployed across critical use cases like Credit, RecSys, GenAI, and real-time inference.
• Address difficult and ambiguous modeling problems that require coordination across various stakeholders (Data, Infra, Product), delivering innovative solutions with a clear focus on medium-term impact.
• Bridge the gap between research and production by designing architectures that respect MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-efficiency.

1. Strategic Impact & Collaboration (Impact)

• Develop and deliver innovative solutions that address project-level challenges, focusing on pushing the latest platform and AI research improvements into downstream production models.
• Actively participate in cross-functional collaborations, ensuring that research outputs are seamlessly integrated into Nubank's decision-making engines.
• Establish technical standards within the AI Core team for experimentation, model evaluation, and code quality, inspiring peers to raise their performance.

1. Mentorship & Function Contribution (Function Contribution)

• Serve as a technical mentor for senior engineers and researchers, providing guidance on deep learning fundamentals, problem formulation, and research methodology.
• Actively contribute to the function's growth by participating in mandatory activities like hiring (interview panels) and leading internal task forces to improve our ML lifecycle.
• Contribute to thought leadership by participating in research collaborations or internal papers that align with Nubank’s strategic goals.

What are we looking for?

• Professional Experience: 5-7+ years in applied AI/ML, with a proven track record of delivering research-driven systems into production environments
• Technical Mastery:
  • Deep expertise in Deep Learning architectures (Transformers, Multimodal, or GNNs).
  • Strong coding skills in Python and proficiency with frameworks like PyTorch, JAX, or TensorFlow.
  • Solid understanding of MLOps and the constraints of deploying models at scale.
• Problem Solving: Sophisticated skills in ML problem formulation and the ability to navigate uncertainty when data is messy or unavailable.
• Communication: Ability to communicate complex technical concepts to both technical peers and cross-functional stakeholders, ensuring alignment and buy-in.
• Analytical Capacity: Experience with large-scale experimentation and A/B testing to validate research hypotheses.

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Please submit your resume in English. Applications in other languages may not be considered.

Bold Metrics is the leading fit and sizing solution on the market today for the world’s top retailers and brands. We are a venture-backed startup that is making a big impact on the environment, forever changing the landscape of eCommerce. We are a remote-first company that is full of inspiring and friendly people.

We are currently searching for a Data Scientist to join our fast-growing team. This position is for someone located in Brazil and working remotely, however if you're located in São Paulo, you will be able to come into the office location as needed. In this position you will have the opportunity to work with some of our biggest projects within the retail industry.

About You:  

You are a humble, passionate, and experienced engineer that is looking for a collaborative and analytical Data Scientist role to support the execution of our product deliveries and machine learning pipeline. This comprises validating the data flow from data sources, analyzing patterns and trends in the data, and facilitating machine learning updates to the system. 

As our Data Scientist, you are an extremely detail oriented, out-of-the-box problem solver with a commitment to doing high-quality work. You will work closely with the Engineering and Data Teams, alongside Customer Success teams to support the flow of data collection and machine learning initiatives to ultimately drive customer success.

How You Will Make an Impact:  

• Lead strategic decision-making for user growth and product innovation by utilizing the full range of data science tools, including analytics, experimentation, forecasting, and machine learning, to enhance the entire consumer experience.
• Develop and deploy machine learning models and causal inference techniques at scale, from concept to measurable business impact.
• Design and oversee experiments and analyses to evaluate product performance and drive continuous improvements.
• Build and maintain automated, scalable data pipelines to support reporting, data visualization, analytics, and machine learning for internal products and solutions.
• Lead the design and management of comprehensive machine learning platforms, ensuring robust model development and deployment processes.

Skills and Qualifications: (even if you do not meet these skills 100%, we still welcome you to apply) 

• BSc or MSc in Mathematics, Computer Science, Engineering or related field.
• Over 3 years of hands-on experience in Data Science, Machine Learning, and Deep Learning.
• +4 years of demonstrated high proficiency in Python and SQL.
• Practical expertise in A/B testing and causal inference.
• Extensive experience with AWS cloud technologies.
• Must have experience and be proficient in MLOps practices, including model deployment and monitoring.
• Experience with Docker for containerization and Git for version control.

About Us: 

Bold Metrics, established in 2017, is a SaaS solution for retailers and brands to reduce returns, improve sustainability and supercharge their supply chain from the ground up. Using a comprehensive set of machine learning and AI technologies to accurately capture customer body measurements, we help apparel brands unlock the power of body data to meet the demands of today's increasingly personalized world. 

Learn more about us at boldmetrics.com

We strive to create a place to work where we all feel safe, empowered, engaged and inspired. We are an equal opportunity employer committed to offering employment that is based upon personal capabilities and qualifications without discrimination based on race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability.