Senior Machine Learning Engineer

About Us Nubank stands as one of the largest digital financial platforms globally, serving over 127 million customers across Brazil, Mexico, and Colombia. With a mission to combat complexity and empower individuals, we are on a journey to redefine financial services in Latin America, and this is just the inception of the vibrant future we are constructing. A…

About UsNubank, established in 2013, aims to liberate individuals from the constraints of slow and inefficient financial systems. By leveraging cutting-edge technology and exceptional customer service, we've redefined how people in Latin America engage with their finances. With operations spanning Brazil, Mexico, and Colombia, Nubank stands as one of the largest digital banking platforms globally. Our listing on the NYSE in 2021 and recognition as one of Time Magazine's 100 Most Influential Companies underscores our commitment to innovation. To learn more, visit www.nu.com.br. About the RoleAs Nubank continues its global expansion, it is vital to uphold high operational standards to empower our customers effectively. This position is pivotal in ensuring that as we scale rapidly, we maintain unwavering resilience. You will serve as the technical leader for our Resilience division. Your role will be instrumental in enhancing operational reliability through collaboration with product teams, implementing best practices, and designing deployment safeguards. You will tackle intricate architectural challenges, mentor fellow engineers, and influence the long-term resilience strategy for one of the world’s leading digital banks.

Tiger Analytics is a leading analytics consulting firm that partners with several Fortune 100 companies, empowering them to derive significant business insights from their data. Our team consists of highly skilled consultants with extensive knowledge in Data Science, Machine Learning, and Artificial Intelligence. We have received recognition from renowned market research firms such as Forrester and Gartner for our innovative approaches and leadership in the analytics space.We are seeking passionate and driven Machine Learning Engineers to join our dynamic team.In this role, you will:Develop and implement solutions for deploying, executing, validating, monitoring, and enhancing data science initiatives.Design scalable and high-performance machine learning systems.Create reusable data pipelines for the seamless integration of machine learning models.Produce high-quality production code and libraries that can be containerized for deployment.

“Transform every logistics journey into a remarkable experience”Company Overview:Established in 2014, Quincus is a pioneering B2B SaaS platform specializing in supply chain operations, with its headquarters in Singapore. Our mission is to tackle the pressing challenges of global supply chains through innovative technology. By leveraging AI and machine learning, we have revolutionized the logistics landscape, providing our clients with unparalleled transparency and efficiency in their supply chain operations.Founded by two visionary entrepreneurs with over a decade of tech experience, Quincus is led by Chief Product Officer Katherina-Olivia Lacey, who champions a tech revolution while promoting women's empowerment within the supply chain sector. CEO Jonathan E. Savoir, recognized in Forbes' 30 Under 30 Asia List in 2020, also contributes to several startup boards, driving innovation forward.Role Overview:Quincus Research is at the forefront of developing the next generation of intelligent systems for our suite of products. We are seeking a highly motivated and skilled Machine Learning Engineer to join our dynamic team. You will play a pivotal role in designing and deploying deep learning and reinforcement learning algorithms at scale. Your expertise will be essential in creating scalable systems for model serving, optimizing inference performance, and managing production workflows.Key Responsibilities:- Design and implement scalable systems for deploying deep learning and reinforcement learning models.- Optimize the inference performance of models through advanced techniques like quantization, pruning, and distillation.- Leverage GPU computing to enhance model training and inference efficiency.- Develop and manage production workflows for the training and deployment of machine learning models.- Collaborate cross-functionally with data scientists and software engineers to create effective machine learning systems.- Monitor and enhance the performance of machine learning models in production.- Stay abreast of the latest advancements in deep learning and reinforcement learning methodologies.

About Pinterest:At Pinterest, we inspire millions worldwide to explore creative ideas, envision new possibilities, and create lasting memories. Our mission is to empower everyone with the inspiration to craft a life they love, and it all begins with our dedicated team.Join a career where you can spark innovation for millions, transform your passion into growth opportunities, celebrate diverse experiences, and enjoy the flexibility to perform at your best. Building a career you love is possible with us.With over 500 million users globally and 300 billion ideas saved, our Machine Learning Engineers at Pinterest create personalized experiences that help Pinners lead fulfilling lives. Our nimble, dynamic teams of just over 3,000 employees are continually growing. At Pinterest, you will gain hands-on access to a vast data repository and contribute to large-scale recommendation systems in unique ways.

Join Stripe as a Machine Learning Engineer focused on supportability. In this role, you will leverage machine learning techniques to enhance product support and improve user experience. You will work collaboratively with cross-functional teams to develop innovative solutions that address customer needs.

Greetings, Future Homie!Join us at Homebase, where we are passionate about empowering small businesses to flourish. Our dynamic team is driven by empathy, urgency, and a bold approach that leads to meaningful outcomes. At Homebase, every team member contributes to elevating our standards, supporting each other, and celebrating our collective successes.We are not merely developing an application; we are fostering unstoppable teams. Are you ready to join us?Your Impact Begins HereAs a Platform Engineer, you will play a key role in designing and implementing components for our data and ML platforms. Your contributions will empower data engineering, data science, and product teams to create features driven by data and machine learning, ensuring that our systems are scalable, reliable, and seamlessly integrated.Architect, develop, and enhance the ingestion processes for large volumes of both structured and unstructured data from a variety of sources.Facilitate data architecture transformation initiatives on Databricks, promoting scalable and efficient systems.Lead the design and implementation of platform components for training, deploying, and monitoring machine learning models in production environments.Provide insights into industry best practices, tools, and technologies in the field of machine learning engineering.Champion continuous enhancements of data and ML workflows through automation and innovative solutions.Own projects end-to-end, ensuring successful delivery from planning to execution.Collaborate with cross-functional teams to gather business requirements and develop effective technical solutions. Key to Your Success - These experiences and strengths will position you for success:Over 5 years of experience in software development, with a focus on data and machine learning.Proficient in SQL, Python, and Databricks.Experience with Airflow, Kafka, and Redshift.Strong skills in data modeling and database design.Expertise in building and deploying machine learning models, including language models.Experience in creating model serving pipelines for batch, streaming, and real-time inference.Demonstrated ability to work collaboratively in a fast-paced environment.

We are seeking innovative and driven Data Scientists with a strong passion for tackling real-world challenges. You will thrive in environments that require working with both structured and unstructured data and will be motivated to develop and deploy scalable machine learning models. This role demands exceptional critical thinking and problem-solving abilities.

About FaireFaire is a revolutionary online wholesale marketplace founded on the principle that the future belongs to local. Independent retailers across the globe generate more revenue than giants like Walmart and Amazon combined. However, they often struggle against these massive entities. At Faire, we harness the power of technology, data, and machine learning to connect this vibrant community of entrepreneurs worldwide. Think of your favorite local boutique; we empower them to discover exceptional products from around the globe to showcase in their stores. With the right insights and tools, we aim to level the playing field, enabling small businesses to compete effectively with larger e-commerce platforms.By fostering the growth of independent businesses, Faire is creating a positive economic ripple effect in local communities globally. We are in search of intelligent, resourceful, and passionate individuals to join us and champion the shop local movement. If you resonate with our commitment to community, we invite you to be part of ours.About this RoleAt Faire, we utilize cutting-edge machine learning and data insights to transform the wholesale sector, empowering local retailers to take on competitors like Amazon and big box stores. Our Data Science team is pivotal in designing and maintaining a diverse array of algorithms and models that drive our marketplace. We are focused on developing machine learning models that enable our customers to thrive.As a vital member of the Brand Data Science team dedicated to Listing Quality, your primary responsibility will be to enhance the quality of product listings, ensuring retailers can efficiently find and evaluate products on Faire. You will employ ML and AI to address significant challenges, including improving image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. Utilizing deep learning, multi-modal LLMs, and human-in-the-loop training, you will create high-performance solutions. This is a rapidly evolving space, and you will be at the forefront of applying the latest technology to drive meaningful real-world impact. You will independently design and implement solutions while collaborating with the cross-functional Listing Quality pod, which includes product, design, engineering, analytics, and operations teams, to resolve challenges comprehensively.

Wisedocs is an innovative and rapidly expanding AI platform that revolutionizes the way insurance companies evaluate claims. With approximately $20 million USD in funding, over 100 team members worldwide, and more than 90 clients across North America and Australia, we are experiencing remarkable growth, doubling our revenue year after year.Founded by industry experts who have firsthand experience with the claims process, Wisedocs merges extensive domain expertise with cutting-edge AI, trained on over 100 million documents. Our platform simplifies complex medical records into clear, structured insights, supported by expert human oversight.Join our mission-driven team dedicated to developing intelligent products that simplify complexity, expedite decision-making, and create a significant impact when it matters most.Role OverviewWe are on the lookout for a Senior Machine Learning Engineer to spearhead the scaling and innovation of machine learning initiatives across the organization. In this pivotal role, you will enhance our inference and training pipelines to accommodate a higher volume of customers while refining extraction and summarization techniques across various modalities. You will foster a customer-centric approach and collaborate with fellow senior engineers to seamlessly integrate the ML system into the broader Wisedocs platform.Our Current ML EcosystemWe have three primary types of ML systems operational in production: an entity classification system, a custom reports generator, and a series of summarization models. Our entity classification has been functioning for four years and currently processes data asynchronously using a combination of models. Discover more about our initiatives at our tech blog.Recent Projects by Our ML Team:Reconstructing our inference pipeline to achieve 100x scalingDeveloping consistent parsing methods for 50,000-page PDFsDeploying our pipeline within an isolated government client environmentYour ResponsibilitiesDesigning and implementing machine learning models to analyze and interpret large sets of medical and insurance documentsCreating robust, scalable APIs using PythonCollaborating with technical stakeholders and leaders to contribute to system design and implementationEnsuring the reliability and scalability of ML systems while enforcing best practices in data engineering and model lifecycle managementWorking closely with our expert-in-the-loop teams to develop industry-leading evaluationsAdditional responsibilities will evolve as projects progress and change

Overview: Join Guidepoint as a skilled Data/AI Engineer and become a vital part of our innovative AI team in Toronto. Our Technology Hub is at the forefront of developing a modern data infrastructure that empowers advanced analytics and promotes responsible AI practices. This strategic initiative is crucial to Guidepoint's vision of harnessing cutting-edge Generative AI and analytical capabilities to enhance our Next-Gen research enablement platform and data-driven products. This role requires remarkable leadership and technical expertise to propel the creation of next-generation research enablement platforms and AI-enhanced data solutions. You will be responsible for designing and scaling Generative AI systems, including large language model (LLM) applications and intelligent research agents, while integrating responsible AI principles and top-tier MLOps practices. As a Senior AI/ML Engineer, you will play a key role in building scalable AI/ML functionalities using Databricks and other advanced tools across Guidepoint’s suite of offerings. The Technology team at Guidepoint thrives on solving complex problems and enhancing user experiences. In alignment with our mission to make individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, our engineering team is tackling challenges to refine internal application architectures and develop new AI-enabled products that optimize our service delivery. This is a hybrid position based in Toronto.

Join Upwork Inc., a global leader in connecting businesses with AI-enabled talent, as a Senior Lead Machine Learning Engineer. In this pivotal role, you will architect and scale the future of agentic intelligence, leading the end-to-end development of AI agents and their underlying platform. From training and evaluating large language models to ensuring runtime orchestration and safety, you will drive innovative solutions that empower both internal teams and external developers to create reliable and high-performing AI agents. This hands-on position blends applied research with platform engineering, making a significant impact on Upwork's mission to transform the workforce for the age of AI.

Join bree as a Machine Learning Engineer, where you will be at the forefront of cutting-edge technology, developing algorithms and models that drive innovation. Collaborate with a dynamic team to enhance machine learning frameworks and contribute to impactful projects that transform data into actionable insights.

Affinity integrates billions of data points from extensive datasets to craft a precise and powerful depiction of the global professional relationship graph. Our users gain essential insights and visibility to cultivate and leverage opportunities within their teams' networks. The position is part of the AI Platform team, responsible for the AI services that drive Affinity's premier relationship intelligence platform. Our work involves extracting and retrieving information from vast amounts of structured and unstructured data to provide actionable insights to our clients. As a Senior Machine Learning Engineer, you'll collaborate closely with data engineers, software engineers, and product managers to shape the future of the leading CRM platform in private capital. Your role will involve designing and building AI systems that efficiently uncover insights from dynamic business interaction data—an exciting and unique opportunity within the sector. This position focuses on applied machine learning with a significant emphasis on engineering rather than research. You will be instrumental in enhancing our ML Engineering capabilities, specifically in information retrieval and ultimately in recommendation systems. Key Responsibilities: Own the full ML lifecycle: Guide projects from ideation to production, encompassing feature engineering, model selection, deployment, and model observability and evaluation. Translate business needs into ML solutions: Gather product requirements and convert them into robust ML system design specifications. Build recommendation and ranking systems: Architect and implement ranking and recommendation infrastructure from the ground up, initially leveraging integrated off-the-shelf models and evolving to tailored solutions over time. Solve complex problems: Tackle diverse challenges in information extraction, storage, and retrieval for both structured and unstructured data. Collaborate cross-functionally: Work alongside cross-functional teams (product, infrastructure, data engineering, and software engineering) to develop robust, high-scale systems that underpin our data processing and ML operations.

Join Lyft as a Data Engineer, where your expertise will drive innovative data solutions that enhance our ride-sharing platform. Collaborate with cross-functional teams to design, implement, and maintain robust data pipelines and architectures that support data analytics and machine learning initiatives.

At GPTZero, we're dedicated to restoring trust and transparency on the internet. As the foremost AI detection platform, we empower educators, students, journalists, marketers, and writers to adeptly navigate the constantly changing landscape of AI-generated content. With millions of users and institutions relying on our services, we're forging a trailblazing company that stands at the crossroads of AI and information integrity.Our team comprises individuals from high-performing engineering cultures, including Meta, Perplexity, AWS, and Affirm, as well as esteemed AI research labs such as Princeton, Caltech, and Vector Institute.What We Are Looking ForAt GPTZero, we are committed to ensuring that machine learning models are developed for the benefit of humanity. In this role, you will contribute to building a next-generation platform aimed at verifying the origin, quality, and factuality of global information. The ideal candidate will have a solid background in machine learning research, an exceptional product sense, and proficiency in software engineering. You will collaborate with a fast-paced team of dedicated innovators, creating industry-defining software that has garnered over 2 million users worldwide. Previous intern projects have been showcased to venture capitalists and state-level policy leaders.ResponsibilitiesDepending on the candidate's strengths, this role can focus more on machine learning engineering or research with an emphasis on publications.Design, train, and fine-tune cutting-edge large language models.Develop AI agents that integrate retrieval-augmented language models.Create efficient and scalable machine learning training and inference systems.Stay abreast of the latest literature and emerging technologies to address novel challenges.Collaborate closely with product and design teams to develop user-friendly applications that drive societal impact.QualificationsProficiency in Python and PyTorch.Experience in pushing the boundaries of machine learning implementation.Self-starter with a strong desire to learn.Highly motivated to contribute positively to society.Ability to adapt and take on multiple roles.Valid work visa for Canada or the US.Bonus:A robust open-source portfolio.Publications in prestigious machine learning venues.

Discover More About Our TeamWe are on the lookout for a talented Machine Learning Engineer to join our Customer Value Forecasting team within the Customer Value Optimization department at HelloFresh. In this role, you will play a pivotal part in developing innovative machine learning products that enhance our value forecasting capabilities. You will tackle advanced forecasting challenges, leveraging AI technologies to produce solutions that directly influence business performance. Your expertise will be critical in designing and constructing scalable, robust, and efficient machine learning systems that can manage vast datasets and complex models.Your ResponsibilitiesWork collaboratively with data scientists and engineers in a cross-functional team to enhance HelloFresh’s value forecasting efficiency.Engage with product managers and business stakeholders to gather requirements and translate them into actionable machine learning products and analyses.Rapidly develop proof-of-concept machine learning models and iterate on them to transition into production-ready solutions with mentorship from senior team members.Assess the performance of machine learning models and provide insights for enhancements.Keep abreast of the latest developments in machine learning and artificial intelligence, proposing and implementing improvements to streamline the machine learning development lifecycle and increase team efficiency.Perform other duties as assigned.Why You’ll Be a Great FitA strong enthusiasm for addressing complex business challenges through machine learning in a dynamic environment. Prior experience in machine learning applications for marketing is advantageous.Proficient programming skills in Python and SQL; experience with PySpark is a bonus.Hands-on experience in designing and maintaining large-scale machine learning systems for production, including model monitoring and drift detection.Quickly adapt to new technologies and modeling methodologies while effectively solving real-world business challenges.A keen interest in utilizing modern data science tools such as cloud development, version control, CI/CD, model registries, and feature stores.Strong communication skills to convey complex technical concepts to both technical and non-technical audiences.What We OfferBox Discount - Generous discounts on one box per week! Enjoy a 75% discount on weekly HelloFresh boxes.

Join Lyft as a Data Engineer and play a pivotal role in shaping our data architecture and infrastructure. You will collaborate closely with cross-functional teams to design and implement robust data pipelines that enable data-driven decision-making across the organization.

Join Opendoor, a dynamic and innovative company transforming the real estate industry through technology. As a Data Scientist, you will leverage your analytical and statistical skills to extract meaningful insights from complex data sets, driving strategic decision-making.