Senior Machine Learning Engineer - Growth

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

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.

About the Role Movable Ink is hiring a Senior Platform Engineer with a focus on Machine Learning for its Toronto office. This role centers on building and improving machine learning features within our marketing technology platform. What You Will Do Work closely with colleagues from different teams to design and implement machine learning solutions that strengthen the platform. Develop and maintain systems that help clients deliver personalized experiences to their audiences at scale. Apply engineering expertise to create reliable, maintainable, and scalable ML infrastructure. Location This position is based in Toronto at Movable Ink.

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.

“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.

Join Mistplay, the leading loyalty app for mobile gamers, as a Senior Machine Learning Platform / Infrastructure Engineer II. At Mistplay, our vibrant community of millions of mobile gamers engages with our platform to discover new games and earn valuable rewards. Players are compensated for their time and investment in gaming, redeeming these rewards for gift cards. Our mission is to enhance the mobile gaming experience for everyone, everywhere! Download Mistplay on the Google Play Store here and connect with us on Instagram, Twitter and Facebook.Important Note: In Canada , Mistplay operates under a hybrid model, requiring 2 days per week in-office presence in Toronto (400 University Ave) & Montreal (1001 Blvd. Robert-Bourassa).

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 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.

Role overview Aerovect is looking for a Machine Learning Operations Software Engineer to join the team in Toronto. The position centers on building and deploying machine learning models that support the company’s products. The main focus is on refining workflows, maintaining model reliability, and contributing to the team’s results. What you will do Develop and maintain systems that handle the deployment of machine learning models Collaborate with engineers and data scientists to improve and streamline machine learning processes Help ensure the performance and reliability of Aerovect’s product offerings Location This role is based in Toronto.

About Boson AI: At Boson AI, we are at the forefront of innovative AI solutions, shaping the future of enterprise AI. Our dedication to advanced AI research, especially in the realms of large language models and agentic systems, empowers us to address intricate real-world challenges for businesses and generate substantial value. Our vibrant and collaborative team of researchers and engineers is committed to pushing the limits of possibility, ensuring that we deliver high-quality, reliable products that integrate seamlessly into enterprise workflows and establish new benchmarks in the industry.About the Role: We are looking for a talented, detail-oriented, and driven Machine Learning Engineer to join our enterprise team. In this crucial position, you will spearhead the development and deployment of innovative AI solutions. This role entails integrating sophisticated language, voice, and vision models, mastering fine-tuning methodologies, constructing advanced workflows and platforms, and pioneering novel agentic strategies. You will engage with challenging problems that require a profound understanding of model behavior, precise implementation, and an unwavering dedication to quality and reliability in enterprise settings. A thrilling aspect of this role is your contribution to the architecture and implementation of intelligent systems where AI agents autonomously execute intricate tasks, interfacing with various data sources and tools, as we collectively strive to build truly integrated and powerful AI capabilities for our clients.

Role overview Stripe is hiring a Machine Learning Engineer in Toronto to help improve the support experience for users. This role centers on applying advanced machine learning methods to make customer interactions smoother and support operations more efficient. What you will do Work with cross-functional teams to design and build solutions that strengthen Stripe’s user support systems. Apply machine learning to real-world support challenges, aiming to improve both customer satisfaction and operational efficiency. Contribute to Stripe’s broader goal of growing the GDP of the internet by making support more effective. Location This position is based in Toronto, Canada.

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.

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

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.

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.

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.