Machine Learning Engineer

Overview In this role you will design, build, and maintain backend services that power ML-driven features at Good Inside. You will integrate ML models and third-party APIs, build data pipelines for model serving and real-time personalization, and ensure scalable, reliable backend systems. You’ll work closely with product, design, mobile, and data teams to translate ML capabilities into user-facing features, contributing to a high-growth platform that helps families. This hybrid role combines strong engineering with practical ML know-how to deliver impactful, personalized experiences. Compensation / BenefitsCompetitive CompensationCompany EquityComprehensive benefits package401k + Company matchTime off to rechargeHybrid work environment ResponsibilitiesDesign, build, and maintain backend services and APIs powering ML-driven featuresIntegrate ML models and third-party ML APIs into production systemsBuild data pipelines and infrastructure for model serving, feature storage, and real-time personalizationCollaborate with product, mobile, and design teams to translate ML capabilities into user-facing featuresOwn reliability, performance, and scalability of ML-adjacent backend systemsDevelop clean, maintainable, and well-documented code aligned with project scopeDocument architectural decisions and handoff materials upon project completionContribute to feature scoping and sequencing to ensure timely delivery of projects Key requirements5+ years of professional software engineering with backend focusExperience shipping ML-powered features in productionWorking knowledge of ML concepts (embeddings, classification, recommender systems, LLMs)Hands-on experience integrating ML APIs and services (OpenAI, Anthropic, ElevenLabs, HuggingFace, AWS SageMaker)Proficiency in Python and/or another backend language (Go, Java, TypeScript/Node)Experience with cloud infrastructure (AWS, GCP, or Azure) and containerized deploymentsFamiliarity with data stores and pipelines for ML (vector databases, feature stores, streaming systems)Excellent interpersonal, verbal, and written communication; strong collaborationSelf-starter with analytical and problem-solving skillsAbility to stay organized in a fast-paced environmentinterpersonal communicationcross-functional collaborationproblem-solvingML concepts (embeddings, classification, recommender systems, LLMs)ML APIs and services (OpenAI, Anthropic, ElevenLabs, HuggingFace, AWS SageMaker)Python or another backend language (Go, Java, TypeScript/Node)