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, 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.
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.
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.
Build and operate the real-time inference service for the risk decision engine with low latency and high availability.
Own model deployment infrastructure including CI/CD, shadow mode, and staged rollouts.
Build model observability and partner with Risk Data Science for production operation.
Mercury is a fintech company that provides banking services for startups via partner banks. The company is committed to creating a safe environment and values diversity, with a growing team focused on 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.
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.
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.
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.
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.
Own end-to-end ML system execution including data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
Architect scalable inference systems, balance latency, cost, and reliability, and deploy production-grade ML solutions.
Gina's Tech Jobs is a recruiting and staffing company that helps firms hire technical talent. They are a small agency focused on IT roles, fostering a high-trust, collaborative environment.
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.
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 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 and operate the ML lifecycle platform, including tooling for experiment tracking, model registry, and versioned pipelines.
Own CI/CD and deployment for ML workloads, building automated pipelines from notebook to production.
Make models observable and reliable in production with monitoring for latency, drift, data quality, and cost signals.
dv01 provides a data analytics platform for the structured finance market, offering transparency into investment performance and risk for lenders and Wall Street investors. With over 400 clients and coverage of over 100 million loans, dv01 is a data-first company with a diverse and innovative culture.
Design, build, and deploy production AI applications, copilots, retrieval systems, and agentic workflows.
Develop backend services, APIs, and application architectures integrating AI capabilities into enterprise systems.
Deploy AI solutions with security, observability, monitoring, evaluation, and governance.
Aimpoint Digital is a data, AI, analytics, and operations research advisory and solution engineering firm that helps organizations design and deploy enterprise-grade AI platforms and production applications. The company is a technical partner focused on moving beyond experimentation, emphasizing strong engineering discipline and scalable architecture.
Build AI platform and production systems supporting computer vision, perception, simulation, and mapping products.
Own critical parts of the AI platform, including orchestration, APIs, and deployment patterns.
Partner with data scientists and simulation engineers to reduce iteration friction and design production architecture.
HERE Technologies is a location data and technology platform company that empowers customers to achieve better outcomes. The company is an equal opportunity employer with a focus on innovation and inclusion.
Build and improve ML components across data, training, evaluation, and inference.
Implement evaluation and testing to understand model behavior.
Debug model issues, performance problems, and production incidents.
This company builds core ML components for large-scale production systems. They emphasize real-world learning, iteration, and collaboration with senior engineers.
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.