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.
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 deploy scalable AI and machine learning architectures using modern frameworks like LLMs and cloud platforms.
Develop, train, and optimize AI models, data pipelines, and AI-powered services with intelligent agents.
Collaborate with technical and business leaders to define AI strategy and translate business objectives into technical solutions.
They build advanced AI-powered systems for automation and business transformation. They offer a remote-first environment with a culture focused on integrity, respect, innovation, and continuous improvement.
Design, build, and deploy production-grade machine learning and AI systems for customer-facing analytics and automation.
Develop and operationalize end-to-end ML workflows from data preparation to model monitoring.
Collaborate with Product and Engineering teams to identify high-impact use cases and deliver AI-powered data products.
Boulevard provides a client experience platform for appointment-based self-care businesses, empowering customers to give clients magical moments. The company values diversity, experimentation, and simplicity, and celebrates diverse backgrounds.
Design, develop, and deploy machine learning and statistical models for forecasting and risk assessment.
Use experimentation and statistical methods to test product changes and improve customer experience.
Analyze large datasets to identify signals, engineer features, and inform model design.
Pipe is a financial technology company that provides a platform for businesses to access capital. It is a fully remote company with a culture of authenticity, humility, and excellence.
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.
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.
Partner with business leaders to identify opportunities and develop analytical strategies.
Create predictive models and scalable machine learning solutions to optimize customer acquisition and retention.
Translate complex data findings into clear business recommendations and drive experimentation.
This company leverages advanced data science and machine learning to solve complex business challenges. It fosters a collaborative and inclusive culture focused on innovation, growth, and teamwork.
Design, build, and deploy machine learning models for cybersecurity use cases like threat detection and risk scoring.
Own the full model lifecycle from data preparation to production deployment, working closely with engineering and product teams.
Build preprocessing and feature engineering pipelines, and monitor model performance with continuous improvement.
SpyCloud transforms recaptured darknet data to disrupt cybercrime. With over 250 employees, it is home to cybersecurity experts protecting businesses and consumers from stolen identity data.
Design, build, deploy, and optimize machine learning models that process large volumes of complex, unstructured data.
Develop and maintain scalable ML pipelines capable of supporting millions of documents and diverse customer requirements.
Lead technical initiatives from early experimentation through production implementation and ongoing improvement.
The company develops intelligent automation solutions using AI and machine learning for large-scale document processing. It offers a highly autonomous engineering environment with a focus on continuous improvement and innovation.
Lead the development and optimization of Large Language Models and Mixture of Experts models.
Collaborate with cross-functional teams to integrate ML models into our platform and conduct cutting-edge research in machine learning.
Mentor junior engineers and contribute to the team’s knowledge sharing and best practices.
webAI is an end-to-end private AI platform that enables enterprises and governments to bring AI to their data, powering specialized intelligence trained on their own knowledge. The company is a dynamic, fast-growing team fostering an exciting and growth-oriented work culture, committed to truth, ownership, tenacity, and humility.
You will build and enhance enterprise SaaS applications across EvolutionIQ and CCC products, spending most of your time writing production code.
You will modernize existing systems by working through complex legacy platforms while contributing to new product development and scalable backend services.
You will leverage AI-assisted and agentic engineering tools to accelerate development, improve engineering productivity, and rapidly prototype new ideas.
EvolutionIQ builds AI that helps insurance claims teams handle claims more accurately, fairly, and efficiently. As part of CCC Intelligent Solutions, they have 40 years of proprietary data and have been named one of Inc.'s Best Workplaces three years running.
Partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten's platform.
Own the journey from initial exploration to production deployment, translating ambiguous goals into reliable services.
Work across product, software development, performance engineering, and customer-facing implementations.
Baseten powers mission-critical inference for dynamic AI companies like Cursor and Notion. They are rapidly growing, recently raised a $1.5B Series F, and foster a collaborative, forward-thinking culture.
Lead complex modeling and analytical initiatives as a technical authority.
Drive modeling strategy and raise technical standards across the organization.
Leverage deep learning and LLMs with traditional methods to deliver real impact.
Gradient AI is a decision-intelligence platform for the insurance industry, using data to reveal risk and improve performance. Backed by $56M in Series C funding, it's a fast-scaling startup with a fun, team-oriented culture.
Design, build, and own agentic systems that produce client-ready financial deliverables from data ingestion to polished output.
Build evaluation and quality systems for generated deliverables, including deterministic checks and model-judged review.
Turn proprietary data into evidence-backed insight by building pipelines that discover and verify patterns.
Farsight is the agentic AI platform for financial services, helping investment banks and private equity firms automate nuanced workflows. The team comes from leading financial institutions and tech companies, focusing on hiring the best to become the best.
Build machine learning and generative AI platforms used across the company.
Create backend infrastructure for scalable, resilient, and high-performance solutions.
Deploy and manage applications in production, coding daily with Python and modern frameworks.
Lyra Health provides evidence-based mental health care, serving over 20 million people globally. The company employs a large workforce and emphasizes a collaborative, mission-driven culture focused on social impact and clinical excellence.
Own ML models across their full lifecycle from data pipelines to deployment and monitoring, ensuring reliable performance.
Run and improve the ML platform including GitOps CI/CD, monitoring serving endpoints, and defining SLOs.
Collaborate with risk, operational, and product teams to turn ML into business value across the organization.
Alma provides installment and deferred payment solutions to help merchants boost sales and customer loyalty, without encouraging bad debt. With over 25,000 merchants, 10 million consumers, 380+ employees, and over €100M ARR, they are a Next40 member scaling rapidly across Europe.
Own productization of Alt's pricing and underwriting models from research through production, keeping them accurate and fast at scale.
Optimize pricing models to reduce infrastructure costs while improving accuracy, especially for high-value assets.
Lead the full ML lifecycle from model training and feature generation to production deployment and monitoring.
Alt unlocks the value of alternative assets, starting with the $5B trading-card market, offering a platform for collectors to buy, sell, vault, and finance their cards. Backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes, the company is at an inflection point with its pricing intelligence infrastructure as a competitive moat.
Architect and build AI platforms, working across distributed teams to deliver GenAI products like Abacus Agents, MCP, and RAG systems.
Develop ML/AI pipelines for data preprocessing, model training, and evaluation, enabling rapid experimentation and self-healing systems.
Mentor software developers, participate in architectural discussions, and communicate technical direction to align teams and stakeholders.
Abacus Insights transforms healthcare data for health plans to improve outcomes, reduce waste, and enhance member and provider experiences. Backed by $100M from top investors, the company is a collaborative, curiosity-driven team of bold individuals embracing AI and automation to innovate in the healthcare industry.
Lead the vision, strategy, and execution of next-generation AI agent technologies within a high-impact cybersecurity environment.
Drive innovation through scalable agentic systems that automate complex workflows and enhance operational capabilities.
Collaborate across engineering, data science, and operational teams to shape AI-driven transformation and measurable outcomes.
Our partner is a cybersecurity company specializing in AI-driven threat research and intelligent automation. They operate in a fast-paced, innovation-focused environment with a remote-first culture.