Role Description As a Senior Machine Learning Engineer (individual contributor) at Revecore, you will: - Use your expertise in machine learning, exploratory data analysis, and software engineering to enhance the productivity and efficiency of our underpayment business. - Work on projects with purpose, such as prioritizing claims based on expected recovery dollars and improving our claim-remit matching process. - Own end-to-end development, training, deployment, evaluation, and improvement of machine learning systems to rank claim opportunities. - Analyze and explore data to identify actionable opportunities from internal and 3rd party data. - Research, implement, and launch new model architectures that drive business impact. - Partner and collaborate with cross-functional teams of software engineers, data engineers, subject matter experts, product managers, and analysts to design and build practical solutions. - Implement cloud MLOps and AIOps best practices to streamline the development, deployment, and maintenance of machine learning models. - Continuously measure the impact of the AI-enabled workflows on key business metrics and use these measurements to improve the machine learning models and workflows. - Learn from and teach your teammates, being the team’s expert in your specialization. - Own a workstream, being the technical lead for the workstream while partnering with others to deliver. Qualifications - A bachelor's degree in any data-centric field; scientific thinking is a must. - Experience working in a similar role, with a focus on machine learning or data science. - Experience developing and deploying machine learning models in a production environment. - Strong experience with Python, including scikit-learn; TensorFlow or PyTorch is a plus. - Ability to wrangle data, perform exploratory data analysis, and draw insights from visualizations. Requirements - An urge to question assumptions and to get it right (or at least good enough) even if your first idea is wrong. - A commitment to collaborate, rather than go off in a corner only to appear when you need to submit a pull request. Benefits - Comprehensive medical, dental, vision, and life insurance benefits from the start of your employment. - 12 paid holidays and flexible paid time off. - 401(k) contributions. - Employee Resource Groups that build community. - Career growth opportunities. - An excellent work/life balance. Work at Home Requirements - A quiet, distraction-free environment to work from in your home. - A secure home internet connection with speeds >20 Mbps for downloads and >10 Mbps for uploads is required. - The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.

Role Description At Keen, the Senior Algorithms Engineer develops, deploys and improves the algorithms that run in Keen AI Cortex. You're a software engineer first, with the understanding of mathematics, data, and inference to read a model spec, question it, and suggest changes the Principal Algorithms Architect hadn't considered. You'll work directly with the Lead Engineer and Principal Algorithms Architect, taking modeling ideas from prototype to production code and contributing to the algorithms when you see a better path. What you’ll do as the Senior Algorithms Engineer: - Own algorithmic features end-to-end across the next generation of Keen's AI Cortex. Design, implement, test, ship, and watch them run in production. - Pitch in on adjacent Python backend projects (Django and FastAPI APIs, AWS infrastructure) when a piece of work spans more than one service. - Keep the engineering practices tight: code review, tests, CI gates, documentation, and a clean ticketed workflow. - Use AI coding tools with judgment. Fast iteration is the point. So is catching the moments when the model is confidently wrong. - Develop algorithms from business ideas and turn them into production code. - Collaborate with others in the development of the solutions, including the ability to effectively push back when the implementation can be improved. - Communicate clearly across Product, Research, and Engineering. Write the design doc, name the tradeoff, get the decision made. Qualifications - 7+ years shipping production Python on a team. - Knowledge of inference methods, particularly in economics and business domains including time-series models (or more generally state-space modeling), probability modeling, and multivariate systems. - Comfortable with the engineering basics: tests, CI, code review, documentation, and working out of tickets. - Hands-on experience with AWS, Docker. - Operates independently. Scopes own work, talks to stakeholders, makes judgment calls when no one else is available to make them. - Writes and speaks clearly. - Math foundation in linear algebra, probability, and statistics. Demonstrated ability to read and write mathematical specifications, interpret and improve documented solutions. - Working knowledge of pandas and NumPy, with understanding of the use of these packages in implementing algorithms. Requirements - Nice-to-have: Marketing Mix Modeling (MMM) or another econometric background. - Bayesian inference experience. - Optimization exposure. - A track record of developing mathematical algorithms into shipped production systems. Benefits - Mentoring and training from people who've been doing this for years. - Hands-on work on Bayesian models, optimization, and the data engineering behind them, applied to a product real customers use. - A seat in conversations across departments and at company-wide meetings. - 4-day work week with 3-day weekends. - Fully remote within the United States.

Role Description The Data group at Weights & Biases works across the full range of data-related topics: - Help business partners set goals, make decisions, and understand the levers to achieve their goals. - Build reporting to keep the business attuned and aligned. - Build datasets and pipelines to support self-service analysis. - Train models to understand customer growth, churn risk, and detect spam and abuse. - Explore novel benchmarks and recommendations for model training. - Build and maintain a massive data platform to power it all. As a Senior Data Platform Engineer, you will: - Partner with other Data Platform Engineers and Data Scientists to expand and maintain our data platform. - Partner with core engineering to improve our product telemetry. - Eventually, join our on-call rotation for the data platform. Strategic goals for the team over the next 12 months: - Migrate data build tools to improve efficiency and performance. - Build a robust internal data catalog and semantic layer to support self-service analytics. - Build an internal AI agent for addressing common data workflows. - Lay the foundations for internal AI applications built on top of our operational data. Qualifications - Deep knowledge (practical and theoretical) of data engineering and the accompanying workflows. - History of writing easy-to-follow code and effective documentation for your projects. - Expert knowledge of data orchestration/data pipeline tools (dbt, dagster, airflow, etc). - Experience working with large and high-demand data warehouses/platforms, multi-PB scale, and extreme business demand for the systems. - Expert knowledge and understanding of web apps and best practices for logging and event instrumentation. - Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge. Requirements - If you work well in a self-directed environment and proactively find ways to improve processes and collaborate with team members or engaged users, your initiative will really shine in this role. - You'll love this role if you enjoy connecting with real users daily, helping them solve issues, and understanding good patterns for using our tools. - Theoretical or practical knowledge of machine learning workflows and terminology. Benefits - Medical, dental, and vision insurance - 100% paid for by CoreWeave. - Company-paid Life Insurance. - Voluntary supplemental life insurance. - Short and long-term disability insurance. - Flexible Spending Account. - Health Savings Account. - Tuition Reimbursement. - Ability to Participate in Employee Stock Purchase Program (ESPP). - Mental Wellness Benefits through Spring Health. - Family-Forming support provided by Carrot. - Paid Parental Leave. - Flexible, full-service childcare support with Kinside. - 401(k) with a generous employer match. - Flexible PTO. - Catered lunch each day in our office and data center locations. - A casual work environment. - A work culture focused on innovative disruption.

Role Description Vor zwei Jahren hätten wir hier einen „TypeScript-Ninja" gesucht. Tiefes technisches Können zählt heute mehr denn je – geändert hat sich nur der Engpass. Es geht nicht mehr darum, wie schnell du tippst, sondern wie gut du beurteilen kannst, was ein Agent produziert. Das Schreiben der Zeilen wird billig; zu wissen, wie gute Software aussieht – saubere Typen, OOP da wo sie trägt, eine Architektur, die hält –, wird zur entscheidenden Fähigkeit. Dazu kommt, was vor und nach dem Code liegt: ein Gespür dafür, was das Produkt wirklich besser macht, und die Fähigkeit, Agents so zu dirigieren, dass am Ende etwas Tragfähiges entsteht. Wir nennen diese Rolle Product Engineer – jemand, der ein Stück Produkt von der Idee bis in Production besitzt, nicht jemand, der Tickets abarbeitet. Du bringst eigene Ideen ein, entscheidest über die Lösung, baust sie mit Agents, verifizierst sie und shippst. Diese Stelle füllst du nicht aus, du prägst sie mit. Qualifications - Software-Engineering-Erfahrung – du hast echte Produkte gebaut und in Production betrieben, idealerweise von 0 auf 1. - Du denkst wie ein Product Engineer – Outcome vor Implementierung. - Du arbeitest schon agentic – du hast mit AI-Coding-Tools gebaut, denkst in Workflows und Kontext. - Bonus: Du baust für Agents, nicht nur für Menschen. - Exzellente schriftliche Kommunikation – Schreiben ist die wichtigste Fähigkeit. - Eigenantrieb und Selbstorganisation – remote, autonom, wenig interne Meetings. - Standort EU – gutes Deutsch von Vorteil. - Menschlich angenehm und verbindlich – das Team muss dich respektieren und sich auf dich verlassen können. Requirements - Logistik- oder Speditionserfahrung – smarte Leute lernen unsere Domäne schnell. - Erfahrung mit dem oben genannten Stack (TypeScript/AWS/React). - Startup- oder Founder-Erfahrung. - Erfahrung im Bauen von Agent-Infrastruktur, Evals oder internem Dev-Tooling. Benefits - Direkter Impact – was du baust, bewegt die Firma. - Attraktives Grundgehalt plus Gewinnbeteiligung über Own Orbit. - Voller Remote-Ortsvorteil, kein Pendeln, freie Arbeitsort-Wahl in der EU. - Die Rolle wächst mit der Firma. - SpaceWalks – Mini-Offsites für echte Verbindung. - MissionDays – Quartalsmeetings in Hamburg. - LogisticsTech Talks mit Top-Speakern aus der Logistik-Tech-Welt. - SpaceCamp – Strategie- und Visionstage. - Async-first: Low/No-Meeting-Kultur intern. - Equipment-Budget für dein Home-Office-Setup. - Wellpass-Mitgliedschaft mit 8.000+ Fitness-, Yoga- und Wellnessangeboten in DE/AT. - Bestes verfügbares AI-Tooling.