Machine Learning Engineer

Good Inside is seeking a Machine Learning Engineer to support ML-driven capabilities in production, distinct from a research or data science-only role. You will build the backend services and APIs that connect machine learning models and third-party ML services to personalized, intelligent user experiences across the Good Inside platform.

This onsite position is based in New York, NY and is designed for engineers who can turn ML functionality into reliable, scalable systems that product, mobile, and design teams can ship to users.

Key Responsibilities

• Design, build, and maintain backend services and APIs powering ML-driven features across the platform
• Integrate and orchestrate ML models and third-party ML APIs (including LLM providers, recommendation engines, and embeddings services) for production use
• Build data pipelines and infrastructure supporting model serving, feature storage, and real-time personalization
• Work closely with product, mobile, and design teams to deliver ML capabilities as user-facing features
• Own reliability, performance, and scalability for ML-adjacent backend systems
• Develop clean, maintainable, and well-documented code aligned with defined project scope
• Create clear documentation of architectural decisions, implementation details, and handoff materials at project completion
• Provide input on feature scope and sequencing to support timely delivery of project outcomes

Required Qualifications

• 5+ years of professional software engineering experience, with strong emphasis on backend development
• Proven experience shipping ML-powered features or products in a production environment
• Working knowledge of ML concepts such as embeddings, classification, recommendation systems, and LLMs (training not required)
• Hands-on experience integrating ML APIs and services (examples include OpenAI, Anthropic, ElevenLabs, HuggingFace, AWS SageMaker, or similar)
• Proficiency in Python and/or another backend language (Go, Java, TypeScript/Node, etc.)
• Experience with cloud infrastructure (AWS, GCP, or Azure) and containerized deployments
• Familiarity with ML-relevant data stores and pipelines (examples include vector databases, feature stores, streaming systems)
• Excellent interpersonal, verbal, and written communication skills
• Strong collaboration and ability to build cross-functional working relationships
• Self-starter with strong analytical and problem-solving skills, plus the ability to stay organized and deliver in a fast-paced environment
• Computer Science degree or equivalent
• At least 2 years of experience in-house as an ML Engineer

Technologies You’ll Work With

• Python, Go, Java, TypeScript/Node
• OpenAI, Anthropic, ElevenLabs, HuggingFace
• AWS SageMaker, AWS, GCP, Azure
• Vector databases, feature stores, streaming systems

Compensation & Benefits

• Base salary: USD 205,000 - 235,000 per year
• Company equity
• Comprehensive benefits package
• 401k + company match
• Time off to recharge
• High-ownership, high-performance, high-collaboration culture

Preferred Background

• Startup growth experience, including enthusiasm for scaling a high-growth organization
• LLM application development experience (prompt engineering, RAG pipelines, conversational AI, or similar)
• Infrastructure and DevOps fluency including CI/CD, monitoring, observability, and ML production readiness
• Prior experience with recommendation systems, personalization engines, or content ranking algorithms in a user-facing product