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.
Collaborate with data scientists and engineers to build scalable ML pipelines, troubleshoot infrastructure issues from Linux to Kubernetes, and optimize model performance.
Drive high engineering standards, design on-premises MLOps solutions, and maintain tools for deployment and monitoring.
Refine CI/CD workflows, incorporate ML model training and evaluation into testing, and ensure seamless handover between research and production.
Learneo is a platform of builder-driven businesses, including Course Hero, CliffsNotes, LitCharts, Quillbot, Symbolab, and Scribbr, focused on supercharging productivity and learning. The company supports high-growth businesses with centralized corporate operations and has a virtual-first culture with employees across multiple countries.
Lead the design and development of scalable AI solutions, from experimentation to production deployment.
Define AI engineering standards and best practices, influencing architecture decisions across teams.
Collaborate with cross-functional stakeholders to integrate generative AI and LLM capabilities into products.
The company is at the forefront of AI-driven product development, focusing on building scalable and intelligent systems. It fosters a culture of innovation and technical excellence, with a remote team and a commitment to engineering leadership.
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, deploy, and optimize production-grade machine learning systems for the full ML lifecycle.
Build scalable MLOps platforms, CI/CD workflows, and model serving infrastructure.
Collaborate with engineering teams to improve platform scalability, security, and operational best practices.
They build scalable MLOps infrastructure for enterprise AI solutions. They foster a collaborative, remote-first culture focused on innovation and professional growth.
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.
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.
Lead complex AI engineering workstreams across multiple business areas and stakeholder groups.
Design and build AI-powered applications using LLMs, agents, and modern architectures.
Establish best practices for prompt engineering, API integrations, and code quality.
The partner company focuses on designing and delivering advanced AI solutions that help organizations transform business processes and create measurable value. It offers a collaborative and inclusive culture with opportunities for career growth and international mobility.
Collaborate with data scientists and software engineers to build scalable data pipelines and ML deployment systems.
Troubleshoot issues across the ML infrastructure stack, from Linux and Docker to Kubernetes and model serving.
Drive high engineering standards through code reviews, testing, and CI/CD enhancements.
Quillbot helps students and professionals strengthen their writing with AI-powered tools. We serve over 56 million users globally and foster a collaborative, virtual-first culture.
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.
Own the ML serving API and deploy models to production with CI/CD and infrastructure as code.
Build monitoring, alerting, and reliability for NBA models and LLM agents.
Drive architectural decisions and mentor engineers on MLOps patterns.
Clutch is a vertical SaaS company backed by Andreessen Horowitz, revolutionizing how credit unions engage with members via fintech lending software. The company is small and ambitious, with a lean data team of five that values pragmatism and fast shipping.
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.
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.
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.
Develop AI-powered applications and workflows from idea to production, balancing quality, latency, reliability, and cost.
Integrate Large Language Models, APIs, RAG approaches, and automation into existing products and processes, learning from real user signals.
Build robust ML pipelines, collaborate with data scientists and engineers, and shape the technical direction for AI solutions.
Breuninger is a fashion and lifestyle company operating 13 department stores and online shops across multiple European countries. With 6,500 employees, the company fosters a friendly, open culture and values innovation in AI and data.
Architect, deploy, and optimize machine learning models for production environments, including search, recommendation, and conversational AI.
Design experiments and analyze large datasets to validate hypotheses and improve product performance.
Collaborate cross-functionally with product managers, engineers, and ML specialists to deliver impactful AI-driven solutions.
This role is listed by Jobgether, a company that uses AI-powered matching to connect candidates with hiring employers. They operate in a remote-first model with a high-performance, collaborative environment, offering opportunities to work alongside top technology professionals.
Provide technical leadership and mentorship to junior engineers on the Applied AI team.
Design and implement scalable architectures for LLM-based applications, including agents and vector databases.
Develop evaluation pipelines and prototype components to validate AI product concepts.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They prioritize fair and efficient recruitment, fostering an inclusive and diversity-driven workplace culture.
Drive end-to-end ML development for customer-facing SaaS products, from pipelines to production deployment and monitoring.
Design evaluation strategies and A/B tests to prove ML features improve customer outcomes and business impact.
Influence product roadmap by communicating ML capabilities and trade-offs to cross-functional teams.
WorkWave provides field service and logistics software solutions that help businesses manage their operations and serve their customers. They are a global company with a remote-first culture, recognized as a Best Place to Work and named among the top software companies worldwide.
Design and deliver production-grade AI/ML and GenAI solutions on cloud platforms like AWS, ensuring scalability and business value.
Act as a senior technical advisor for enterprise customers, translating challenges into secure, cost-efficient cloud architectures.
Develop reusable frameworks and best practices from delivery work to scale successful solutions across customers.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. The company operates with a global, remote-first team focused on efficient recruitment.
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.