Lead the technical vision and roadmap for the ML platform.
Partner with Product and Engineering leadership to align investments.
Establish MLOps practices and optimize large-scale model training and serving.
The hiring company builds machine learning platforms and MLOps solutions for large-scale AI development. It offers a collaborative and specialized environment with a focus on technical excellence and innovation.
Design, deploy, and maintain scalable ML infrastructure for model training, batch processing, and real-time inference.
Build and manage cloud-based infrastructure with AWS and Snowflake using Infrastructure-as-Code practices.
Develop CI/CD pipelines, automation frameworks, and monitoring for ML systems to improve reliability and governance.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They operate with a team-oriented culture and offer remote work flexibility, focusing on efficient, unbiased recruitment.
Design, develop, and deploy foundational AI and ML models, building robust, scalable pipelines for advanced analytics.
Champion top-tier coding, testing, and MLOps practices, navigating ambiguity to refine pipelines and elevate workflows.
Partner with cross-functional stakeholders to convert strategic needs into technical specs and embed ML features into live applications.
Wave helps small businesses thrive so the heart of our communities beats stronger. They create an environment buzzing with creative energy and inspiration, valuing boldness, quick learning, and generous knowledge sharing.
Build end-to-end Machine Learning pipelines, including data preparation, code optimization, automated model training, and prediction workflows.
Provide technical leadership in MLOps processes, establishing best practices for development, deployment, and maintenance.
Design and implement cloud-based architectures for AI and data solutions using platforms such as GCP, AWS, or Azure.
A technology company specializing in data-driven solutions for consumers, leveraging AI and cloud technologies to transform data into insights. The company fosters a dynamic, innovation-driven culture with a remote-first approach, collaborating across multidisciplinary teams.
Design and maintain ML model productionization infrastructure for high-visibility product features.
Collaborate with data science to streamline model training, validation, and deployment.
Implement robust monitoring and alerting for model performance, drift, and data quality.
The Athletic is a sports media company powered by one of the largest global newsrooms in sports, delivering in-depth coverage of professional and college teams across North America and Europe. With over 500 full-time staff, they foster a collaborative culture focused on high-quality journalism and data-driven innovation.
Design and implement scalable real-time data integration and Change Data Capture (CDC) solutions using the Striim platform.
Build proof-of-concepts, reference architectures, and deployment patterns for enterprise implementations.
Collaborate with Engineering, Product, and GTM teams to validate architectural designs and improve platform capabilities.
Striim is a unified data integration and streaming platform that connects clouds, data, and applications with real-time analytics for enterprise customers. It is a Silicon Valley startup with a culture fostering entrepreneurship and growth, operating as one team with unlimited potential and dignity.
Design and build scalable backend services for ML feature management, storage, and serving.
Own technical initiatives from design through implementation, balancing trade-offs and navigating ambiguity.
Collaborate with cross-functional teams to define solutions that align with business objectives and improve platform reliability.
The company is a technology firm focused on building scalable machine learning platforms and intelligent decision-making systems. It operates in a remote-first environment with a collaborative culture and a commitment to engineering excellence.
Lead the design and development of cloud-native AI solutions using Microsoft Azure and large language models.
Build AI-powered capabilities like RAG, prompt orchestration, and intelligent automation.
Establish engineering standards and collaborate with security teams to ensure compliance.
Our partner is a company that builds cloud-native AI solutions to empower internal teams and accelerate innovation. They have a remote-first engineering team and offer competitive benefits.
Lead the development and improvement of MLOps platform capabilities supporting machine learning workflows across Oura.
Drive design and unification of workflows and tooling for reliable training, orchestration, and deployment of ML systems.
Partner with data scientists and engineers to improve the end-to-end ML lifecycle, including governance and maintainability.
Oura empowers people to own their inner potential through its award-winning Oura Ring and app, providing daily health insights. As a quickly growing company, we focus on team well-being and helping people live healthier, happier lives.
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.
Develop highly scalable and reliable data systems on AWS cloud platform for data-centric products.
Collaborate with Data Science teams to incorporate Machine Learning algorithms using Python and data engineering tools.
Lead and mentor team members, contribute to Agile cycles, and ensure timely delivery of documented software.
Experian is a global data and technology company that powers opportunities for people and businesses worldwide. With 22,500 employees across 32 countries, they foster a culture of innovation and data-driven solutions.
Design, build, and operate scalable backend services, APIs, and data pipelines for ML-driven personalization.
Improve reliability, performance, and observability of production ML systems, including model versioning and safe rollout.
Collaborate with data scientists and product engineers to translate business needs into robust technical solutions.
Hungryroot uses AI to build a consumer-centric food and wellness company, acting as a personal assistant for healthy living by recommending and delivering healthy groceries, recipes, and supplements. They are a distributed team across 28+ US states with a remote-first culture emphasizing collaboration, flexibility, and an annual company retreat.
Design, build, and operate the online feature store serving ML features to production models with low latency and high reliability.
Build and maintain data pipelines (batch and streaming) that compute, validate, and publish features from source systems.
Act as a technical leader for feature store infrastructure, partnering with Data Science and Engineering teams to drive quality and scalability.
Forward Financing is a financial technology company on a mission to unlock capital for small businesses across America. The company has provided over $3.5 billion in funding to 71,000+ small businesses and is recognized as a Best Place to Work, with a culture focused on employee investment and customer experience.
Design, build, deploy, and maintain scalable machine learning and AI systems in GCP to solve complex business problems and create new value.
Partner across teams to understand problem definitions, data needs, and solution approaches, and support model deployment with MLOps practices.
Take ownership of production issues, perform root cause analysis, and improve documentation and quality assurance processes for ML systems.
General Mills makes food the world loves, operating across 100+ markets. As a large company, it prioritizes being a force for good and fosters a culture of bold thinking and big hearts, where employees challenge each other and grow together.
Design, build, and operate large-scale ML solutions for ad delivery performance.
Collaborate with cross-functional teams to deploy models into production.
Mentor peers and contribute to ML best practices and AI-native development.
The company is a technology firm focused on AI-driven advertising solutions. It operates in a remote-first environment with a collaborative and inclusive culture.
Build, train, and deploy machine learning models and data pipelines using Python, pandas, NumPy, and scikit-learn, ensuring scalability and reliability in production.
Design, implement, and continuously improve LLM-powered applications and Retrieval-Augmented Generation (RAG) pipelines, including prompt engineering, embedding strategies, and vector store integration.
Conduct exploratory data analysis and design data visualizations to uncover trends and communicate key metrics to both technical and non-technical stakeholders.
Great Gray Group is a leading independent provider of trustee and administrative services for Collective Investment Trusts, with over $370 billion in assets under management. They are a high-growth organization backed by Madison Dearborn Partners, fostering a culture of collaboration, innovation, and continuous improvement.
Drive AI platform architecture and execute the long-term roadmap for machine learning and generative AI.
Lead AI infrastructure vision including end-to-end training, fine-tuning, and low-latency inference platforms.
Set engineering excellence standards for the full AI/ML SDLC and mentor senior engineers.
Lyra Health is a leading provider of evidence-based mental health care, serving over 20 million people globally. The company operates with a focus on transformative care and has delivered over 15 million sessions, employing a large team that includes engineers, data scientists, and clinical professionals.
Own end-to-end delivery quality for major engagements, translating ambiguous client needs into practical execution plans.
Lead solution architecture and technical decision-making, making pragmatic tradeoffs between speed, quality, and client value.
Build and ship production AI/ML systems using Python, ML frameworks, and cloud-native infrastructure while mentoring other engineers.
Eliza is a technology services company and Advanced-tier OpenAI partner that helps organizations build and deploy AI solutions, from generative AI to predictive analytics. They are a collaborative, mission-driven team focused on real-world AI impact.
Design and maintain CI/CD and MLOps pipelines for AI and software applications, ensuring seamless deployment and automation.
Build and scale cloud-native infrastructure using Kubernetes, Docker, and GPU clusters to support high-performance AI workloads.
Champion Infrastructure as Code and observability practices to ensure high availability, security, and compliance across multi-cloud environments.
Bitdeer is a world-leading technology company providing AI and Bitcoin mining infrastructure. Headquartered in Singapore, the company has a global presence with data centers in multiple countries and a culture focused on innovation and reliability.
Set technical direction across multiple services and teams as a senior individual contributor.
Define AI platform patterns including agent orchestration, tooling, governance hooks, and evaluation surfaces.
Stay hands-on, designing and building production systems in Python across the AI stack.
Mitratech builds world-class products that simplify operations in Legal, Risk, Compliance, and HR functions. Serving 20,000 client companies globally, including 30% of the Fortune 500, the company fosters a diverse, inclusive culture that blends entrepreneurial spirit with enterprise investment.