Build and maintain data pipelines for analytics, ML, and product applications.
Design scalable data infrastructure with a focus on quality and observability.
Collaborate with cross-functional teams to understand data needs and implement solutions.
Prolific builds human data infrastructure to power the next wave of AI innovation. They are a remote-first company focused on ethical data collection and mission-driven culture.
Lead and develop a high-performing team of MLOps engineers, fostering technical excellence and collaboration.
Define and execute the MLOps roadmap, aligning infrastructure initiatives with research, engineering, and product goals.
Design and maintain scalable ML infrastructure including automated training pipelines, CI/CD, and model serving platforms.
Our partner is a company focused on cutting-edge machine learning infrastructure for large-scale AI systems. They foster an inclusive, mission-driven culture with international collaboration and value innovation, diversity, and continuous learning.
Design and run Kubernetes environments optimized for AI inference, retrieval, and agent execution in secure settings.
Deploy and operate open-source model stacks, model gateways, vector databases, and supporting platform components.
Build reproducible platform automation using Infrastructure as Code and GitOps approaches for stable, auditable delivery.
Deutsche Telekom IT Solutions Slovakia provides innovative information and communication technology services. It has grown to become the second largest employer in eastern Slovakia with over 3900 employees, focusing on continuous transformation and improvement.
Design and build scalable backend services using Python, AWS, and Kubernetes to improve developer productivity.
Lead technical initiatives across the engineering organization with 7–10 years of experience.
Work on production AI/LLM applications and microservices architecture in a fully remote European team.
Codeminders develops cutting-edge software solutions for high-tech companies, focusing on AI, mobile apps, video conferencing, and cloud computing. They collaborate with world-class engineers from the US and Ukraine and uphold strong ethical standards with no business ties to Russia or Belarus.
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 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.
Partner with analytics, marketing, and product teams to understand data needs and build systems for AI applications to access trusted data at scale.
Define standards, infrastructure, and governance for AI-driven experiences, ensuring data reliability, security, and usability.
Drive projects from design through production deployment, implementing data security and governance practices for sensitive data.
Rula is a mental healthcare company dedicated to treating the whole person with evidence-based, compassionate care. They are a remote-first organization with a focus on diversity, equity, and inclusion, hiring in most US states.
Design, build, and operate scalable cloud infrastructure using Kubernetes, Terraform, and modern infrastructure-as-code practices.
Improve and evolve cloud networking architecture, including VPC/VNet design, peering, routing, DNS, TLS, ingress/egress, and load balancing.
Contribute to system reliability through on-call support, incident response, root cause analysis, and performance optimization.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They use automated review and matching to ensure fair candidate evaluation.
Build, implement, and deploy agentic platforms within client environments, focusing on scalable AI-driven solutions.
Design and build agentic platforms using Python and modern AI frameworks like LangGraph, CrewAI, and AutoGen.
Integrate agentic platforms with client systems, including APIs, data platforms, cloud services, and enterprise applications.
Nearform is an independent team of data & AI experts, engineers, and designers who build intelligent digital solutions and capability at pace. Today, our team of 500 experts in 20+ countries is trusted by leading enterprises, including Lululemon, Puma, Sun Life, Starbucks, Travelex, Virgin Media 02, and Walmart.
Build and scale data infrastructure powering targeting, identity, and measurement capabilities.
Optimize core ETL/ELT pipelines and ensure operational reliability with documented SLAs.
Implement privacy-compliant data methodologies meeting GDPR/CCPA standards.
Kargo creates powerful moments of connection between brands and consumers to build businesses. With 600+ employees and offices across the US, UK, Australia, and Ireland, they take a creative science approach to deliver unique ad experiences across premium platforms.
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.
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.
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.
Productize deployment, security, and scaling of Applied AI solutions with automation and security guardrails.
Mistral provides full-stack AI solutions from frontier models to developer tools, applications, and compute, partnering with enterprises across high-stakes industries. It is a dynamic, collaborative team with a diverse workforce distributed globally, known for being creative, low-ego, and team-spirited.
Build and operate production-grade model serving infrastructure using vLLM, TGI, or Triton frameworks.
Design and implement auto-scaling, multi-model architectures, and intelligent request routing for ML inference.
Optimize GPU utilization, memory efficiency, and observability to ensure low-latency, cost-effective systems.
They are a distributed cloud infrastructure startup building AI-native cloud services with GPU-powered compute. The company is well-funded, fast-scaling, and operates in a remote-first environment with a focus on sustainability and decentralization.
Own and evolve data infrastructure including Supabase, n8n workflows, HubSpot integrations, and pipelines connecting external platforms.
Take technical ownership of the content factory: tooling, automation pipelines, and agent orchestration for scalable production.
Reduce manual overhead by building automations and agent workflows that replace repetitive processes.
Platform Engineering is home to the world's largest community of platform engineers, connecting thousands of professionals through events like PlatformCon with over 35,000 participants annually. The team fosters a low-ego, async culture and operates fully remote across Europe.
Design, build, and maintain scalable batch and streaming data pipelines.
Develop reliable ETL/ELT workflows using Python, Spark, and modern orchestration tools.
Improve data quality, validation, monitoring, and observability across the platform.
The company is a Berlin-based, remote-first technology company building advanced market intelligence and software solutions for the automotive industry. It operates in a stable growth phase with an established product and a strong technical team.
Lead the strategic vision and execution of a unified data organization spanning Data Engineering, Data Science, AI, and Business Intelligence.
Shape scalable data platforms, drive AI innovation, and build high-performing teams that transform complex data into measurable business value.
Define technical roadmaps, establish best practices, and collaborate with senior stakeholders to support business growth.
Our partner is a company looking for a Head of Data & AI based in Germany. The size and culture are not specified, but the role is in a fast-paced, innovation-driven environment with a focus on data and AI.
Own core compute infrastructure across multiple cloud providers and regions.
Design capabilities for greater performance and flexibility in service deployment.
Investigate and resolve challenging cloud and compute issues across the stack.
Render is a cloud platform for developers building AI-native, full-stack, multi-service applications. Trusted by over 6 million developers, the company has raised $257M in funding and values craft, velocity, and user experience.
Own end-to-end technical execution for strategic customer and partner engagements, including discovery, infrastructure design, implementation, and production deployment.
Design and build cloud infrastructure supporting advanced AI workloads, including simulation, training, evaluation, inference, and large-scale batch processing.
Improve platform reliability, security, performance, and cost efficiency by debugging issues across application, network, storage, compute, and orchestration layers.
The partner company is building the infrastructure foundation for next-generation AI applications and physical AI workloads. The engineering team is pioneering and values ownership, technical excellence, and solving challenging engineering problems at scale.