Develop, deploy, and maintain machine learning models in production environments using AWS SageMaker or similar platforms.
Perform exploratory data analysis, feature engineering, and build data pipelines to support scalable ML workflows.
Monitor production models, address performance issues, and collaborate with engineering and business stakeholders to deliver data-driven solutions.
Google is a global technology company that develops products and services to organize information and make it universally accessible and useful. The company is a large multinational with a culture focused on innovation, collaboration, and data-driven decision-making.
Design, build, and optimize data workflows for Machine Learning and GenAI solutions in cloud environments.
Develop and deploy Machine Learning and Generative AI models using AWS SageMaker.
Create and manage data and model pipelines to improve the efficiency of AI and machine learning systems.
Netrix Global provides the people, processes, and technology to run and scale modern data-driven businesses. It is a top system integrator with a culture focused on ownership, teamwork, and respect.
Design and maintain scalable ML infrastructure including data pipelines, training workflows, and model deployment systems.
Own end-to-end ML lifecycle operations, ensuring reliable delivery of models into production at scale.
Implement monitoring, telemetry, and feedback loops for ML models running across large-scale device fleets.
Our partner company develops ML systems for connected hardware products used by customers worldwide. They operate in a fast-paced, product-driven environment with a collaborative and technically ambitious culture focused on real-world ML impact.
Lead the design and operation of production machine learning systems for batch and online use cases with a focus on reliability and scalability.
Build and improve ML lifecycle infrastructure including training pipelines, inference workflows, monitoring, and automation.
Partner with cross-functional teams to translate business problems into ML solutions and guide prototypes to robust production systems.
Included Health is a healthcare company delivering integrated virtual care and navigation, aiming to raise the standard of healthcare for everyone. They are a remote-first organization offering comprehensive benefits and fostering a culture of inclusion.
You will experiment with emerging technologies and contribute to building new models and systems.
You will implement prototypes in Python and focus on delivering solutions to production.
You will partner with the platform engineering team to streamline MLOps workflows and maintain high code quality.
Verve creates a more efficient and privacy-focused way to buy and monetize advertising by fusing data, media, and technology. With 30 offices globally, they serve top advertisers and publishers and foster a collaborative, fun culture.
Build models and data products that go from prototype to production, including generative models and subscriber-behavior predictions.
Dig into large, messy datasets to uncover trends and patterns, and contribute to the core Python data science library.
Build LLM-powered pipelines and agents, with comprehensive evals to validate model responses.
DevSavant is an operating partner for startups and growth-stage companies, helping them turn ambition into execution. With over 8 years in venture-backed ecosystems, they are trusted to accelerate delivery and scale teams efficiently.
Design, build, and automate enterprise-grade AWS SageMaker environments to support scalable machine learning initiatives.
Develop and implement DevOps automation for SageMaker Unified Studio and related cloud infrastructure.
Build and optimize CI/CD pipelines for deploying custom Docker images, kernels, and machine learning workloads.
This role is listed on behalf of a partner company that builds and optimizes enterprise-scale machine learning infrastructure. They operate with a collaborative international team and modern engineering practices.
Design and maintain scalable data pipelines for ingestion, transformation, and delivery into data warehouses, feature stores, and ML/AI systems.
Build workflows for processing unstructured data and develop semantic representations to enable advanced search, retrieval, and LLM-powered applications.
Collaborate with stakeholders to translate business requirements into scalable data and ML solutions.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They use technology to review applications and share top-fitting candidates directly with employers, ensuring a fair and efficient hiring process.
Develop highly scalable and reliable data systems on AWS cloud platform for data-centric products.
Collaborate with Data Science teams to incorporate Machine Learning algorithms using Python and data engineering tools.
Lead and mentor team members, contribute to Agile cycles, and ensure timely delivery of documented software.
Experian is a global data and technology company that powers opportunities for people and businesses worldwide. With 22,500 employees across 32 countries, they foster a culture of innovation and data-driven solutions.
Design, build, and maintain scalable data and ML pipelines for analytics and AI systems.
Build and optimize workflows for structured and unstructured data, enabling semantic search and RAG use cases.
Manage and optimize vector databases and indexing strategies for efficient retrieval and AI-powered search.
This is a partner company seeking a Data & Machine Learning Engineer based in Brazil. They operate in a highly technical and global environment with strong emphasis on scalability, performance, and innovation.
Design and develop ML/AI models including predictive and LLM-based systems.
Optimize algorithms and perform data cleaning, feature engineering, and model validation.
Collaborate with clients and internal teams to translate results into insights.
Digica is an AI and software company delivering intelligent software across AI domains, focusing on deep learning and computer vision. They work with global companies and startups, and foster a growth-oriented, innovative culture.
Own the full data science engine for a priority vertical from business problem to deployed model, driving measurable revenue and media efficiency.
Deliver buying models that maintain positive ROAS and quality across Insurance and Advertiser Quality.
Establish trusted, direct partnership with vertical business stakeholders and produce validated, documented output.
Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.
Design, build, and ship ML models that power content generation and quality eval scoring for Canva's generated element and template library.
Own the full ML lifecycle — from data pipelines and training through to deployment, monitoring, and iteration.
Partner with Content Engine, CORE AI Research, AI Media, and Discovery teams to align ML work with the broader content strategy.
Canva is redefining how the world experiences design with its intuitive design platform. We serve hundreds of millions of users globally and foster a culture of flexibility, inclusion, and innovation.
Build ML infrastructure for low-latency model deployment, distributed inference pipelines, and real-time telemetry.
Scale ranking systems by moving models from experimentation to production, optimizing latency and cost trade-offs.
Implement model CI/CD for automated versioning, canary releases, hot-swappable container rollouts, and zero-downtime rollbacks.
Sequen provides an integrated platform that pairs cutting-edge frontier ranking models with infrastructure to run them in production at sub-10ms latency and enterprise scale. They are a small, highly technical, early-stage team focused on turning recent AI advances into production-grade systems.
Build and iterate on end-to-end ML solutions for misdirected email detection.
Collaborate cross-functionally to turn customer needs into product improvements.
Run rigorous experiments and evaluations to ensure reliable detection.
Abnormal protects organizations from AI-powered cybercrime using its behavioral AI platform. Trusted by 4,500+ enterprises, the company focuses on securing email, identity, and AI systems.
Design, build, and deploy production-grade machine learning and AI systems for customer-facing analytics and automation.
Develop and operationalize end-to-end ML workflows from data preparation to model monitoring.
Collaborate with Product and Engineering teams to identify high-impact use cases and deliver AI-powered data products.
Boulevard provides a client experience platform for appointment-based self-care businesses, empowering customers to give clients magical moments. The company values diversity, experimentation, and simplicity, and celebrates diverse backgrounds.
Design, train, and evaluate machine learning models to address business problems.
Build and maintain data pipelines and infrastructure for model development and deployment.
Deploy ML models into production and monitor performance, reliability, and drift.
Critical Software delivers software solutions and consulting in complex, business-critical environments across industries like aerospace, defense, and healthcare. They are a Benefit Corporation committed to positive impact and an equal opportunity employer.
Own productization of Alt's pricing and underwriting models from research through production, keeping them accurate and fast at scale.
Optimize pricing models to reduce infrastructure costs while improving accuracy, especially for high-value assets.
Lead the full ML lifecycle from model training and feature generation to production deployment and monitoring.
Alt unlocks the value of alternative assets, starting with the $5B trading-card market, offering a platform for collectors to buy, sell, vault, and finance their cards. Backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes, the company is at an inflection point with its pricing intelligence infrastructure as a competitive moat.
Design, build, and operate reliable, scalable backend services and data pipelines.
Work across our cloud infrastructure (AWS) to ship and run production systems.
Improve the performance, reliability, and observability of the systems you own.
Allocate is transforming private market investing by enabling RIAs and family offices to seamlessly discover, model, and manage their private market exposure. They are a company that values world-class client experience, challenges convention, and embraces continuous improvement and meritocracy.
Own the end-to-end data science lifecycle for moderately complex models, from data ingestion to deployment and monitoring.
Apply expertise in machine learning and statistics to solve marketplace problems, including bidding, yield modeling, and experimentation.
Mentor junior data scientists and influence technical decisions within the team.
OpenX focuses on unleashing the economic potential of digital media companies by building digital advertising markets and technologies. The company is a growing and scaling team that values thoughtful, creative executors and a blend of market design, technical innovation, and operational excellence.