Machine Learning Engineer - Enterprise

We are seeking dedicated Machine Learning Engineers with a passion for developing innovative systems utilizing large language models (LLMs) and real-world data. In this dynamic role, you will collaborate with clients and team members to design, prototype, and implement scalable machine learning solutions that drive results.Join our high-performing, collaborative team that prioritizes clear communication, practical execution, and continual learning. If you excel in fast-paced environments, enjoy solving complex problems, and are committed to the quality and impact of your work, we would love to hear from you.

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

At Cerebras Systems, we are revolutionizing AI technology with the world's largest AI chip, which is 56 times larger than traditional GPUs. Our innovative wafer-scale architecture equips users with the computational prowess of multiple GPUs on a single chip, simplifying programming tasks. This groundbreaking approach enables unparalleled training and inference speeds, allowing machine learning practitioners to seamlessly operate extensive ML applications without the complexities of managing numerous GPUs or TPUs. Cerebras proudly serves an impressive clientele, ranging from leading model laboratories to major global enterprises and pioneering AI startups. A testament to our capabilities, OpenAI has recently forged a multi-year partnership with Cerebras, aimed at delivering 750 megawatts of scale and transforming critical workloads through ultra-fast inference. Our state-of-the-art wafer-scale architecture empowers Cerebras Inference to provide the fastest Generative AI inference solution globally, boasting speeds over ten times faster than GPU-based hyperscale cloud inference services. This extraordinary increase in speed is redefining user experiences with AI applications, enabling real-time iterations and enhancing intelligence through additional agentic computation.About the RoleWe are on the lookout for a dynamic and seasoned engineer to join our Inference Core Model Bringup team. This team is tasked with the rapid deployment of advanced open-source models (such as LLaMA, Qwen, etc.) or proprietary models provided by customers on our Cerebras CSX systems. Success in this role necessitates a systems-oriented generalist who flourishes in fast-paced environments and is adept at navigating the entire Cerebras software stack. Your contributions will be instrumental in achieving unprecedented performance, efficiency, and scalability for AI applications.

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.

“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.

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.

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.

About maneva maneva builds AI systems for manufacturing, using vision and production data to reduce downtime, improve quality, and support worker safety through automation on the factory floor. Role Overview This contract position calls for a Machine Learning Engineer / Research Engineer to join maneva's research and engineering efforts. The role involves close collaboration with a lead researcher and robotics engineers to advance industrial automation solutions. What You Will Do Work alongside a lead researcher to guide modeling choices, run structured experiments, and contribute to academic paper development. Implement and maintain policy training code for methods such as ACT, Diffusion Policy, Pi0 fine-tuning/OpenPi, and baseline techniques. Independently investigate and apply new methods from recent academic literature. Run ablation sweeps, prepare comparison tables and plots, and analyze results to extract insights. Maintain an evaluation harness to support reproducibility across experiments. Conduct literature reviews and organize documentation for ongoing and completed work. Draft and refine technical writing, including methods, experiments, and related work sections. Review training code written by robotics engineers as needed. Location Remote , Toronto, Ontario, Canada

LOCATION: This position can be based anywhere in Canada, with a preference for candidates situated in the eastern or central time zones to facilitate collaboration with our teams in the US, Europe, and India.ABOUT THE ROLEWiser Solutions is on the lookout for a Principal Machine Learning Engineer to lead and implement our AI and data science strategy. This senior technical leadership position requires an individual with profound expertise in machine learning, data science, and production engineering, complemented by the business insight needed to translate complex capabilities into customer value.As the technical authority for AI at Wiser, you will set architectural direction, communicate our capabilities to customers and partners, and deliver production systems that yield measurable business outcomes. This role demands proficiency in both strategic planning and hands-on implementation, allowing you to present to executives while also debugging production pipelines in the same week.We are cultivating an AI-native engineering culture at Wiser, where AI tools and techniques are integral to our workflows, not just the products we develop. We need a Principal AI Engineer who not only delivers AI products but also exemplifies AI-enhanced work methodologies and aids the broader engineering team in their adoption. If you are passionate about the transformative potential of AI in software development and implement that transformation in your daily activities, we want to hear from you.What You Will DoStrategic LeadershipDefine and enhance Wiser's AI and data science technical strategy in collaboration with product and business leadership.Articulate Wiser's AI capabilities to customers, partners, and advisors—clarifying our approach, roadmap, and unique offerings.Identify high-impact opportunities where AI can solve customer challenges or provide a competitive edge.Develop technical standards, patterns, and best practices that shape engineering decisions across the organization.Technical ExecutionArchitect and build production AI systems, including LLM applications, RAG pipelines, semantic search, and traditional ML models.Create rigorous evaluation frameworks, experimentation methodologies, and monitoring systems that ensure AI solutions yield reliable, measurable results.Integrate classical data science methods (statistical modeling, experimentation design, feature engineering) with modern generative AI approaches.Oversee technical quality for AI systems across the board: from data pipelines to model deployment and production observability.Cross-Functional ImpactCollaborate with product management to convert business requirements into technical solutions and validate these solutions against customer needs.Mentor and elevate the AI/data science team (3-5 engineers), enhancing the technical capabilities of the team.

LOCATION: This position can be based anywhere in Canada, with a preference for candidates in the Eastern or Central time zones who can collaborate effectively with our teams across the US, Europe, and India.ABOUT THE ROLEWiser Solutions is on the lookout for a dynamic Principal Machine Learning Engineer to lead and execute our AI and data science strategies. This senior-level technical leadership role demands an individual with profound knowledge in machine learning, data science, and production engineering paired with the business insight required to turn complex capabilities into tangible customer value.As the technical authority for AI at Wiser, you will guide architectural direction, represent our capabilities to clients and partners, and oversee the delivery of production systems that yield measurable business benefits. This role necessitates the ability to seamlessly transition from strategic planning to hands-on implementation, capable of presenting to executives while also troubleshooting production pipelines within the same week.At Wiser, we are cultivating an AI-native engineering culture where AI tools and techniques are integrated into our daily operations, not just the products we create. We seek a Principal AI Engineer who not only delivers AI solutions but also exemplifies AI-enhanced methodologies, supporting the broader engineering team in their adoption. If you believe in the transformative power of AI in software development and embody that transformation in your work, we want to hear from you.What You Will DoStrategic LeadershipDefine and evolve Wiser's AI and data science technical strategy in collaboration with product and business leadership.Articulate Wiser's AI capabilities to customers, partners, and advisors, outlining our approach, roadmap, and unique selling points.Identify significant opportunities where AI can address customer challenges or provide a competitive edge.Establish technical standards and best practices that guide engineering decisions across the organization.Technical ExecutionArchitect and develop production AI systems, including LLM applications, RAG pipelines, semantic search, and traditional machine learning models.Create robust evaluation frameworks, experimentation methodologies, and monitoring systems to ensure AI solutions deliver reliable and measurable outcomes.Integrate classical data science techniques (statistical modeling, experimentation design, feature engineering) with contemporary generative AI methodologies.Oversee the technical quality of AI systems from data pipelines through to model deployment and production observability.Cross-Functional ImpactCollaborate with product management to translate business requirements into technical solutions, validating them against customer needs.Mentor and uplift the AI/data science team (3-5 engineers), raising the technical standards across the board.

Join Fullscript as a Senior Machine Learning EngineerAt Fullscript, we’re revolutionizing health technology with a commitment to enhancing patient care. Established in 2011, our mission is straightforward: to empower practitioners with easy access to trusted products, enabling them to provide superior care.Our platform has evolved to support over 125,000 practitioners, offering clinical insights, lab interpretations, patient analytics, and access to premium supplements. More than 10 million patients depend on Fullscript to maintain their care plans and achieve their health goals.We develop innovative tools designed to simplify healthcare, making it smarter and more personal. By consolidating everything practitioners need in one place, we enable them to concentrate on what truly matters: helping people get better.Your Opportunity Awaits.Bring your creativity, dedication, and compassion to our team. Join us in shaping the future of healthcare.We're on the lookout for a Senior Machine Learning Engineer to join our dynamic AI team. In this role, you will spearhead the development of cutting-edge AI features that enhance clinicians' services and empower patients to achieve better health outcomes.

Join HelloFresh as a Senior Machine Learning Engineer within our Growth Tech Alliance! In this pivotal role, you will design and implement the robust infrastructure that powers our innovative marketing systems. You will transition algorithmic prototypes into high-performance production systems, enabling our AI-driven marketing optimization to operate reliably and independently on a global scale.About the TeamWe are looking for a Senior Machine Learning Engineer who can elevate our AI tools by constructing and deploying a resilient infrastructure for our intelligent marketing optimization systems. You will play a crucial part in executing our AI initiatives, developing scalable microservices for predictive scoring, and orchestrating complex LLM-based agents for creative intelligence. As the ML engineering leader, you will facilitate the evolution of algorithmic prototypes into high-performance production systems, ensuring maximum speed and agility as we redefine how HelloFresh automates marketing at an unprecedented scale.ResponsibilitiesCreate robust integration layers for visual AI pipelines that handle multi-modal embeddings driving various predictive models.Convert proof-of-concept models into resilient production microservices while architecting LLM-based orchestration frameworks.Develop high-throughput, low-latency data pipelines to process first-party data and channel signals to external platforms like Meta and Google.Collaborate with cross-functional teams of data scientists and engineers to enhance HelloFresh’s value forecasting efficiency.Establish CI/CD processes, feature stores, and drift detection mechanisms to guarantee continuous delivery and model reliability.Undertake additional duties as assigned.

Cresta is dedicated to transforming customer interactions into a strategic edge by harnessing the full potential of contact centers. Our innovative platform merges advanced AI capabilities with human intelligence, enabling contact centers to uncover valuable customer insights, streamline conversations, automate inefficient processes, and empower team members to enhance productivity. Founded by visionary leaders from the esteemed Stanford AI lab, including Sebastian Thrun, known for his groundbreaking work with Google X and Waymo, Cresta's leadership also features Ping Wu, co-founder of Google Contact Center AI, and Tim Shi, an early member of OpenAI.Embark on an exhilarating journey with us to redefine the workplace through AI. The future of work is unfolding at Cresta.About the Role:The Knowledge Assist (KA) team at Cresta is at the forefront of developing AI solutions tailored for the contact center industry, with a primary focus on enhancing agent productivity by ensuring access to the right knowledge at the right moment.Current projects include:Generative Knowledge Assist (GenKA): Provides real-time, context-aware suggestions for contact center agents, integrating multiple knowledge bases to facilitate quick information retrieval and ensure accurate responses.Knowledge Search (KS): A custom search experience designed specifically for contact center agents, built on the GenKA infrastructure, with aspirations to evolve into a comprehensive enterprise search solution.Retrieval-Augmented Generation (RAG): A pivotal initiative supporting GenKA and KS, focusing on efficient retrieval of relevant knowledge and generating ready-to-use responses based on this knowledge.Our internships are set in a dynamic, fast-paced environment where collaboration with top researchers and engineers is encouraged. Interns will have the opportunity to contribute to significant AI research and implement innovative techniques at scale.This internship offers a rare chance to influence the future of AI at Cresta by tackling complex challenges and introducing groundbreaking AI advancements into real-world applications.

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.

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.

Role overview sia is hiring a Generative AI Consultant in Toronto. This role centers on designing, building, and improving generative AI models that address real business challenges. The consultant works closely with colleagues from different backgrounds to deliver solutions that matter to clients. What you will do Collaborate with cross-functional teams to develop and refine generative AI models Apply advanced AI technologies to meet specific client needs Translate complex data into practical insights for business decision-making Support clients in reaching their strategic goals through AI-driven solutions

At d-Matrix, we are pioneering the potential of generative AI to transform the technology landscape. Positioned at the cutting edge of both software and hardware innovation, we continuously strive to expand the horizons of what can be achieved in this dynamic field. Our workplace culture is built on the principles of respect and collaboration.We emphasize the importance of humility and open communication. Our inclusive team thrives on diverse perspectives, which lead to innovative solutions. We are on the lookout for motivated individuals who are passionate about overcoming challenges and are driven by tangible outcomes. Are you ready to explore your playground? Together, we can unlock the infinite possibilities of AI.Job Title: Software Engineering Intern - KernelsLocation: Toronto, CanadaProgram Duration: 12 weeks: June 1st - August 21st or June 22nd - September 11thProject Overview:As a Software Engineering Intern on our Kernels team, you will have a significant impact on the development of high-performance kernels that are crucial for accelerating machine learning models. Your role will encompass creating reference implementations for accuracy verification, defining unit tests for the implemented operators, optimizing performance, conducting scalability analysis across varying problem sizes, and packaging and shipping the final implementations. You will also gather performance metrics and identify bottlenecks to enhance core functionality.What You Will Do:Implement high-performance kernels using low-level languages (Assembly/ISA experience is a plus).Develop, test, and optimize kernels for machine learning models and performance.Automate the creation of reference implementations and unit tests.Analyze scalability and performance, collect metrics, and troubleshoot bottlenecks.Package and share implementations with partner teams.

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. As a publicly traded company on the New York Stock Exchange (NYSE: NU), we leverage proprietary technology, advanced data intelligence, and a streamlined operating model to provide financial products that are straightforward, accessible, and human-centric. Our contributions to the financial sector have garnered recognition from esteemed global rankings such as Time's 100 Companies, Fast Company's Most Innovative Companies, and Forbes' World’s Best Bank. Explore more about our team and opportunities at Careers at Nubank. About the Role Data forms the cornerstone of Nubank’s AI and machine learning models, allowing millions of customers to access equitable financial products. As a Lead Machine Learning Engineer within the AI Core Data Intelligence team, you will engage in a diverse range of activities—from constructing scalable data infrastructures and feature pipelines that support our cutting-edge foundation models to designing, training, and deploying transaction classification models that enhance crucial customer experiences throughout the organization. Your role will be pivotal at the convergence of data and applied machine learning, contributing to various phases of the ML lifecycle: acquiring and labeling data, training and assessing models, and assisting in deployment and production monitoring through rigorous quality controls. Collaboration with product, compliance, and ML teams will be essential to ensure that models are auditable, respect privacy, and yield measurable business value. Joining our team means being part of the data engineering backbone of AI Core, where you will ensure data is accessible, healthy, and accurately tracked across our entire ML ecosystem. Here, you will merge your skills in building scalable data systems with your enthusiasm for machine learning, crafting solutions that enable our models to learn from richer, higher-quality data. Learn more about our work in the AI Core team on our blog: Understanding Our Customers' Finances Through Foundation Models.

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.