Develop and deploy machine learning and AI systems.
Work with LLMs, generative AI, and modern ML frameworks.
Optimize model performance, latency, and cost.
A fast-growing technology company building critical infrastructure that powers high-volume, real-time business operations across multiple systems and platforms. It is a collaborative, fast-moving environment where engineers have meaningful influence on architecture and product direction.
Build and operate the real-time inference service that scores models for the risk decision engine, with low latency and high availability.
Own model deployment infrastructure including registry, versioning, CI/CD, and staged rollouts.
Build model observability with availability, latency, error monitoring, and drift detection.
Mercury is a fintech company that builds banking services for startups. They are committed to diversity and inclusion, and are an equal opportunity employer.
Own the full lifecycle of production machine learning models from handoff to deployment and monitoring.
Ensure model reliability through drift detection, performance monitoring, and incident response.
Extend the shared ML platform to make it stronger and cheaper for future models.
CarOnSale is the AI-powered platform for B2B used car trading in Europe, connecting over 40,000 buyers from 20+ countries. We are a team of engineers and data scientists building the operating system for the industry, with a culture of direct ownership and short decision paths.
Drive and continuously improve MLOps practices across the machine learning environment.
Build, optimize, and maintain CI/CD pipelines using GitLab for reliable ML delivery.
Productionize and maintain machine learning models using AWS, with a focus on SageMaker.
The company operates a globally deployed recommender system and focuses on machine learning infrastructure. The team is collaborative and supportive, with an emphasis on knowledge sharing and professional development.
Architect and develop robust, end-to-end machine learning solutions, managing the complete ML lifecycle from development to production.
Collaborate closely with data engineers and data scientists to create highly scalable solutions and integrate them across the software development life cycle.
Evaluate cloud solutions for performance and cost-efficiency, and communicate technical concepts clearly to stakeholders and teams.
Coderio designs and delivers scalable digital solutions for global companies, combining strong technical expertise with a product mindset to lead complex software initiatives end-to-end. They work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
Design, build, and improve production agentic AI systems used to solve complex real-world problems.
Develop agent architectures, model integrations, and evaluation frameworks for reliable, production-grade AI.
Build scalable APIs, services, and infrastructure supporting agent execution and AI-powered product experiences.
Air is the leader in Enterprise Readiness, providing an AI-native platform to align development, production, delivery, and sustainment for government agencies and industrial suppliers. The company is a startup with a focus on mission-driven work and innovation.
Develop tools and automate manual processes to improve operational efficiency and accelerate experimentation.
Build, integrate, and monitor end-to-end lifecycles of large-scale distributed machine learning systems.
Enhance ML pipelines for forecasting platforms with automated retraining and deployment.
Apella applies computer vision and machine learning to improve the standard of care in surgery. They are a remote-first startup focused on building reliable ML solutions for healthcare.
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.
Own the ML/AI platform, including training infrastructure, model serving, inference pipelines, and production integrations.
Set technical direction for ML/AI architecture, tooling, standards, and strategy in partnership with data science and engineering.
Drive GenAI and LLM engineering, including RAG, prompt engineering, fine-tuning, and agentic workflows.
This company builds AI/ML infrastructure for financial technology products used by over 1,600 financial institutions. It operates as a globally distributed team with a focus on innovation and collaboration.
Productionize ML models into reliable, scalable systems with CI/CD, data versioning, and model governance.
Implement monitoring for data quality, drift, model performance, and pipeline health with clear alerting.
Refactor research code into reusable components and enforce engineering best practices.
Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years, backed by Spark Capital & Foundry.
Own the ML/AI platform including training infrastructure, model serving, inference pipelines, and production integration.
Drive the GenAI/LLM strategy including retrieval architectures, evaluation harnesses, and agentic workflows.
Partner with data scientists, DevOps, and backend engineers to productionize models and define API contracts.
SavvyMoney is a US-based financial technology company providing integrated credit score and personal finance solutions to over 1,600 banks and credit unions throughout the United States. The company was recognized as a 'Top 25 Places to Work' in the San Francisco Bay Area and is an Inc. 5000 Fastest Growing Company.
Design, build, and productionize ML models for ETA prediction using regression, classification, and time-series forecasting.
Develop NLP/LLM-based extraction pipelines for message-based status updates, including text extraction and entity recognition.
Own models end-to-end from data pipeline to deployment and monitoring, turning noisy logistics data into scalable solutions.
FourKites is the leader in AI-driven supply chain transformation, providing real-time visibility and an Intelligent Control Tower that breaks down enterprise silos. The company processes over 3.2 million supply chain events daily, serving 1,600-plus global brands, and fosters a collaborative culture with a focus on diversity and inclusion.
Design, develop, and deploy AI/ML models including NLP, predictive models, and intelligent automation workflows.
Integrate LLM-powered features using APIs like OpenAI and implement RAG patterns and AI agent workflows.
Collaborate with cross-functional teams to translate requirements into AI use cases and contribute to engineering best practices.
We are a confidential US-based organization dedicated to leveraging AI and technology to drive business transformation. Our team values innovation and collaboration, and we foster a culture that supports employee growth and responsible AI practices.
Build AI-powered tools and copilots across the SDLC to reduce cognitive load and eliminate manual steps.
Research and deploy GenAI solutions to improve delivery pipelines and system reliability.
Collaborate with Platform, SRE, and DevOps teams to integrate intelligent automation into the core engineering platform.
Coderio designs and delivers scalable digital solutions for global companies. They combine strong technical expertise with a product mindset and value autonomy and clear communication.
Design, build, and improve machine learning training and inference pipelines for AI-driven music experiences.
Apply machine learning and prompt engineering across complex ML pipelines to support large language model features.
Create evaluation frameworks with LLM-as-judge pipelines to measure quality and enable rapid iteration.
Spotify is a digital music service that provides access to millions of songs. With over 700 million monthly active users, Spotify fosters a culture of innovation and collaboration, prioritizing artist-first principles in its AI music lab.
Build the environments and verifiers our models train against
Own the synthetic data pipeline, from generation through quality gates
Ship models into production and keep improving them on real usage
LiveKit builds the infrastructure layer for the voice-driven era of computing, enabling developers to build, deploy, and scale voice AI applications. Founded in 2021, they power voice AI for major companies and have a small, senior team that values craft and creativity.
Design, build, and operate end-to-end ML systems across batch and real-time workloads.
Develop production capabilities for personalization, recommendations, optimization, and experimentation.
Provide technical leadership for ML architecture and distributed systems.
Kard is building commerce media infrastructure that connects financial institutions, financial-services platforms, and merchants through data and merchant-funded rewards. It is a remote-first company that values initiative, openness, and humility.
Design, build, and deploy generative AI systems using large language models, RAG, and agentic workflows.
Own the full lifecycle from experimentation to production, including evaluation, infrastructure, and monitoring.
Collaborate with Product, Engineering, and Data teams to turn AI ideas into scalable, secure customer experiences.
Typeform is a form builder that helps over 150,000 businesses collect data with forms, surveys, and quizzes that people enjoy. With 500 million responses annually, we are a diverse team of 500+ employees committed to excellence, respect, and transparency.
Drive backend development for AI workflows using Python and FastAPI as part of a collaborative team.
Productionize LLM integrations with systems for Bedrock usage, quotas, retries, and cost controls.
Build for scale by optimizing async job orchestration, performance, and data-layer for petabyte-scale enterprise data.
Smarsh empowers organizations to manage risk and uncover intelligence in digital communications. With over 6500 clients in regulated industries and consistent recognition from Gartner and Forrester, Smarsh has been listed on the Inc. 5000 as one of America's fastest-growing companies since 2008.
Own the development, fine-tuning, and evaluation of in-house AI models from dataset design through to production deployment.
Run supervised fine-tuning and post-training experiments, establishing benchmarks and evaluation harnesses.
Take models to production on Stream's serving stack, tuning for latency, cost, and reliability at high volume.
Stream provides APIs and SDKs for building activity feeds, chat, and voice/video, powering over a billion end users worldwide. We are a team of over 120 peers from over 35 countries, with a casual social culture that values transparency and excellence.