Source Job

• 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.

• 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.

• Lead the design and operation of production machine learning systems for batch and online use cases with a focus on reliability and scalability.
• Build and improve ML lifecycle infrastructure including training pipelines, inference workflows, monitoring, and automation.
• Partner with cross-functional teams to translate business problems into ML solutions and guide prototypes to robust production systems.

Included Health is a healthcare company delivering integrated virtual care and navigation, aiming to raise the standard of healthcare for everyone. They are a remote-first organization offering comprehensive benefits and fostering a culture of inclusion.

• 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 algorithmic features end-to-end across the next generation of Keen's AI Cortex, from design to production.
• Pitch in on adjacent Python backend projects (Django, FastAPI, AWS) when work spans multiple services.
• Collaborate across Product, Research, and Engineering, writing design docs and making tradeoff decisions.

Keen Decision Systems provides an AI-driven marketing platform that empowers marketing leaders and finance teams to make data-driven, future-focused business decisions. As an Inc. 5000 Fastest-Growing Private Company and a Triangle Business Journal Top 10 Best Place to Work, we promote a Conscious Culture with a 4-day work week.

• Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency.
• Deliver buying models that maintain positive ROAS and improve lead quality across a portfolio of brands.
• Establish trusted, direct partnership with business stakeholders and identify net-new modeling opportunities.

Launch Potato is a profitable digital media company that connects consumers with leading brands through data-driven content and technology. With a remote-first team spanning over 15 countries and reaching 30M+ monthly visitors, they have a high-growth, high-performance culture focused on speed, ownership, and measurable impact.

• Lead strategic discovery and AI solutioning for global accounts, architecting state-of-the-art AI solutions on the Celonis platform.
• Drive end-to-end execution of high-stakes Proof-of-Value projects, delivering scalable AI systems with advanced RAG and agents.
• Act as a trusted advisor to C-suite executives, ensuring value realization and adoption of transformative AI solutions.

Celonis is the global leader in Process Intelligence and process mining technology, helping enterprises unlock productivity by placing intelligence at the core of business processes. As one of the fastest-growing enterprise SaaS companies, Celonis has more than 20 offices worldwide and fosters a mission-driven, inclusive culture.

• 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.

• 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.

• 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.

• Define the architecture and contracts for ML serving, feature store design, and model composition.
• Lead the buildout of a unified serving stack to streamline model deployment from training to production.
• Architect backfill and evaluation infrastructure to enable rapid model iteration.

Airbnb connects hosts offering unique stays and experiences with guests worldwide. With over 5 million hosts and 2 billion guest arrivals, we foster a culture of belonging and innovation.

• 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.

• Build and ship ML models to help customers search and find answers about their financial lives.
• Develop user and product embeddings, contextual bandits, and personalized ranking algorithms.
• Work with a modern cloud-native data platform to deploy models to millions of customers.

Monzo is on a mission to make money work for everyone, offering personal and business bank accounts, savings, investments, and pensions with a focus on solving problems and changing lives. With over 15 million customers and a culture of innovation, Monzo prioritizes diversity and inclusion.

• Own the gold data layer by transforming silver tables into curated, semantically rich datasets for AI model development.
• Reverse-engineer data semantics by collaborating with product engineers, clinical experts, and analyzing SQL queries and stored procedures.
• Build pipelines for reuse, automate quality filtering and synthesis, and maintain reproducible dataset snapshots.

PointClickCare is a leading health tech company that helps providers deliver exceptional care through AI and data. Privately held and founder-led, they serve over 30,000 organizations, were recognized as a top private cloud company by Forbes, and have one of Canada's Most Admired Corporate Cultures.

• 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.

• Optimize production LLM serving with vLLM and SGLang to maximize throughput and minimize latency through batching and quantization.
• Profile training runs to find bottlenecks and resolve them with attention implementations like FlashAttention on H200 and GB200 hardware.
• Deploy and operate multiple models on shared GPU clusters with autoscaling, bin-packing, and efficient handling of mixed workloads.

Egen is a fast-growing technology company with a data-first mindset, partnering with clients on Google Cloud and Salesforce to drive action through data and insights. We are a team of dedicated engineers who thrive on solving tough problems and continually innovate to achieve fast, effective results.

• 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, build, and maintain scalable machine learning infrastructure on AWS, including training and deployment pipelines.
• Develop and deploy ML models for recommendation systems, fraud detection, credit risk, and personalization use cases.
• Implement monitoring, logging, and alerting systems to ensure model performance, stability, and reliability in production.

Our partner is a fast-growing, innovation-driven company where machine learning and AI systems directly power large-scale fintech and commerce experiences. They foster a highly dynamic environment with strong emphasis on experimentation, rapid iteration, and measurable business impact.

• Develop, deploy, and maintain machine learning models in production environments using AWS SageMaker or similar platforms.
• Perform exploratory data analysis, feature engineering, and build data pipelines to support scalable ML workflows.
• Monitor production models, address performance issues, and collaborate with engineering and business stakeholders to deliver data-driven solutions.

Google is a global technology company that develops products and services to organize information and make it universally accessible and useful. The company is a large multinational with a culture focused on innovation, collaboration, and data-driven decision-making.