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.
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.
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.
Build and maintain scalable machine learning solutions in production.
Train and validate deep learning and statistical models for real-world applications.
Partner with product managers and engineers to define requirements and drive ML roadmap.
Twilio is a cloud communications platform that empowers businesses to build personalized customer experiences through APIs. With thousands of employees worldwide, the company champions a remote-first culture focused on inclusion and innovation.
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.
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.
Design and develop machine learning models for localization workflows, including machine translation and LLM finetuning.
Implement and optimize models using Python, TensorFlow, and deploy via Docker and AWS services.
Evaluate and select ML techniques, perform statistical analysis, and maintain clear documentation.
Welo Global is a leader in multilingual AI, technology, and content solutions serving over 2,000 clients in 300 languages. The company combines globally scaled multilingual infrastructure with a network of over 500,000 linguists and domain experts, backed by seven ISO certifications.
Design, build, and maintain scalable machine learning infrastructure on AWS, including training and deployment pipelines.
Develop and deploy ML models for recommendation systems, fraud detection, credit risk, and personalization use cases.
Implement monitoring, logging, and alerting systems to ensure model performance, stability, and reliability in production.
Our partner is a fast-growing, innovation-driven company where machine learning and AI systems directly power large-scale fintech and commerce experiences. They foster a highly dynamic environment with strong emphasis on experimentation, rapid iteration, and measurable business impact.
Design and develop machine learning solutions ensuring accuracy, performance, security, and scalability
Implement and maintain end-to-end AI/ML pipelines from data ingestion to deployment
Collaborate across planning, design, and code review to raise overall code quality
We shape the future of communications from remote-first environments. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide, with a strong culture of connection and inclusion.
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.
Build, ship, and own product features end-to-end using cutting-edge AI/ML techniques.
Apply classical ML and LLM-based approaches like RAG, prompt engineering, and fine-tuning to enhance the audit and risk platform.
Collaborate with cross-functional teams in an Agile environment to deliver scalable, production-quality code.
Optro is a leading audit, risk, ESG, and InfoSec platform trusted by over 50% of the Fortune 500. The company has been named one of the 500 fastest-growing tech companies in North America for seven consecutive years, fostering a culture of innovation and collaboration.
Own end-to-end Machine Learning (ML) system execution including data pipelines, training, and deployment.
Fine-tune and adapt models using state-of-the-art methods like LoRA and DPO.
Architect scalable inference systems and collaborate closely with application engineering.
This company develops advanced production-grade machine learning systems. The team is small and high-trust, with a culture of ownership and pragmatism.
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.
Design and build scalable ML training, deployment, and inference pipelines using CI/CD and cloud infrastructure.
Implement MLOps for model versioning, monitoring, and automated retraining to detect drift and performance degradation.
Partner with Data Scientists and Product teams to productionise models and integrate ML into customer-facing products.
We develop solutions that make an impact for companies around the globe. Our culture embraces openness, acts with respect, shows grit & guts, and combines employment with enjoyment.
Lead development of core machine learning systems, fine-tuning LLMs and building NLP pipelines to extract data from insurance documents.
Architect training workflows using user feedback, and build intelligent agents for complex web interfaces.
Design evaluation pipelines and scalable systems for training, inference, and feedback in a fully remote role.
Total Performance Consulting provides AI, consulting, software development, and nearshore staffing services. The company operates with a small, fast-moving team and works on meaningful problems alongside its founders.
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.
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.
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.
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.