As a member of this team, you will directly influence the company’s operations, collaborating closely with stakeholders from Revenue, Finance, and Product teams. You will also drive enhancements to our customer-facing billing and usage systems, ensuring accuracy, reliability, and a seamless experience. Responsibilities include designing, implementing, and maintaining backend services and APIs, ensuring high performance, scalability, and security for Billing and Internal Systems.
Andesite is looking for a strong Senior Machine Learning Engineer who has a proven track record of delivering AI/ML products at scale. You will help build and iterate on a production agent architecture involving LLMs, RAG, and context/memory management. You will also be responsible for developing other models as needed to support evolving product requirements. Work closely with product managers, product developers, threat analysts, data scientists, and other engineers to understand the business requirements and translate them into ML solutions.
🦅 US
🏖️Unlimited PTO👶10w maternity👨👧10w paternity
Andesite is seeking a Senior Machine Learning Engineer to deliver AI/ML products at scale, design, develop, and deploy agentic AI involving LLMs, RAG, and context/memory management, manage AI/ML infrastructure and lifecycle, and collaborate within a cross-functional team. The candidate will also keep pace with research in machine learning, large language models, and cyber security.
Your mission as a Senior Engineer is to develop features and solutions that meet the strategic goals and needs of the business, deliver high-quality code that follows best practices, ensure systems are reliable and maintainable, guide team members, and engage with the engineering community.
As a Senior Software Engineer on the XCore team working on the Admin Platform, you will help acquire and retain customers for life by building and maintaining the services, APIs, and databases that will power a self-service mode for Customer Admins. Working across Engineering teams, you will maintain and enhance our existing services for management and configuration of all the customization that Admins can do.
Focus on recommender systems modeling at the intersection of generative recommenders and foundational understanding of user taste across music and talk content formats. Collaborate with a cross-functional team to define and execute the machine learning technical strategy for the product area, building the next generation of Spotify content and user representations and the technical architecture to support it.
This role will advance Omada's platform and enablement for analytics, data science, and AI initiatives by designing and building scalable, efficient platforms and architectures. It focuses on creating the technological foundation that empowers analytics, machine learning, and data-driven decision-making across the organization, maintaining reliable infrastructure for AI/ML workloads, using MLOps/LLMOps, automation, and cloud-native technologies.
Design, build, evaluate, and ship ML solutions in Spotify’s personalization products and collaborate with cross functional teams to build new product features that advance the mission to connect artists and fans. Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users. Promote and role-model best practices of ML systems development throughout the organization and be part of an active group of machine learning practitioners.
Design, develop, test and deploy high-quality services, applications and APIs as an individual contributor on an agile, cross-functional team. Drive technical discussions around architecture, scalability, security and performance; propose improvements and enforce best practices. Implement backend services in Scala/Java (Spring Boot) and frontend components in React.
A key component of this team's domain is a graph database used as the foundation in unlocking complex data relationships to drive innovative AI features across the organization. Along with the graph database, the learn team offers full stack ownership, building and maintaining intuitive frontend interfaces along with robust backend services all leveraging modern AWS cloud technologies. This breadth of work fosters a deep sense of ownership, rapid iteration, and the ability to deliver impactful work.