Design and operate core AI platform components for training, deploying, and serving ML models at scale.
Own model serving and inference workflows end-to-end, optimizing for reliability, latency, throughput, and cost.
Collaborate with product, infrastructure, and security teams to build scalable platform capabilities for AI-powered features.
Mozilla Corporation is the non-profit-backed technology company behind Firefox and Pocket, with over 225 million monthly users. A wholly-owned subsidiary of the Mozilla Foundation, the company is mission-driven, employee-owned, and focused on privacy and open standards.
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.
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.
Develop and refine features for deep learning models using large-scale customer and behavioral datasets.
Implement model architecture changes informed by recent academic research from venues like NeurIPS.
Optimize model training pipelines for efficiency and scalability while collaborating with client teams.
OpenTeams builds AI that empowers, offering energy-efficient and cost-effective models with a commitment to open source. The company values freedom, teamwork, accountability, and quality, and reinvests 3% of profits into the open-source community.
Design, build, and deploy AI/ML solutions from prototype to production for client business problems.
Apply generative AI and LLMs, establishing MLOps best practices including CI/CD and model monitoring.
Serve as a trusted technical advisor, translating ambiguous problems into well-scoped solutions and presenting to stakeholders.
DevIQ builds modern cloud and data solutions for mid-market companies focused on energy reduction, healthcare, education, and smart cities. The company offers competitive benefits, a strong team culture, and opportunities to work on end-to-end solutions with multi-disciplinary teams.
Design, implement, and refine machine learning models for personalized recommendations.
Improve architecture, code structure, and performance of ML systems, raising engineering quality.
Investigate research papers and lead experiments to validate and ship state-of-the-art models.
Canva is redefining how the world experiences design, providing a platform that empowers users to create stunning visuals. As a large, global company with campuses in Sydney and Melbourne, it fosters a culture of creativity, collaboration, and flexibility.
Design, train, evaluate, and ship ML systems for governance and security, starting with prompt injection detection and behavioral anomaly detection.
Build supporting infrastructure including data pipelines, feature stores, model serving, and evaluation harnesses.
Set technical direction for ML work, own architecture, evaluation methodology, and model lifecycle.
Docker provides developer tools for building, sharing, and running applications across Docker Desktop, Docker Hub, and Docker Scout. With over 20 million monthly users and a globally distributed remote-first team, Docker is trusted by solo founders to the world's largest companies.
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.
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.
Design and build systems that improve the efficiency of ML training and inference workloads.
Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
Reddit is a community of communities built on shared interests, passion, and trust, hosting the most open and authentic conversations on the internet. With over 100,000 active communities and approximately 126 million daily active users, Reddit is one of the internet's largest sources of information.
Developing and iterating on embedding models for advertising use cases, from aggregation pipelines to sequence models.
Building data processing and inference pipelines and evaluating features through end-to-end experimentation.
Ensuring reliability and scalability of ML systems by writing tests, monitoring, and reviewing code.
Reddit is a platform of communities built on shared interests and authentic conversations. With over 100,000 active communities and 126 million daily active users, it is one of the largest sources of information on the internet.
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.
Lead applied ML initiatives for identity verification, focusing on computer vision models like face liveness detection and anti-spoofing.
Build, train, and optimize deep learning models and pipelines on AWS with strong reproducibility and monitoring.
Collaborate across teams to ensure ML solutions meet privacy, compliance, and reliability requirements.
Mitek is a global leader in digital and biometric identity authentication, fraud prevention, and mobile deposit solutions, serving over 7,500 organizations worldwide. The company is headquartered in San Diego with operations across multiple countries and emphasizes a Virtual 1st culture, valuing flexibility 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.
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 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.
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.
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.
Develop and operate production-ready AI and machine learning systems for enterprise-scale products.
Build and optimize LLM-powered applications, RAG pipelines, and intelligent agents.
Implement software engineering best practices for AI development including CI/CD and testing.
Our partner is building enterprise-grade AI solutions that deliver measurable business impact. They offer a remote-friendly work environment with a collaborative engineering culture focused on innovation, quality, and continuous learning.
Lead and grow a cross-functional team of ML engineers, backend engineers, and data analysts.
Guide research and experimentation, balancing long-term innovation with near-term business impact.
Partner with Product and Engineering leaders to identify opportunities for increasing revenue and conversion through personalization.
Constructor is an AI-first ecommerce search and discovery platform helping shoppers find products and enabling global e-commerce brands to drive revenue and conversion. The company offers a fully remote team, unlimited vacation, and a training budget.