Good Inside is hiring a Machine Learning Engineer for a production-focused engineering role at the company’s New York, NY onsite office. This position is centered on building and maintaining backend services and APIs that support ML-driven features, including model integration and scalable delivery of personalized experiences.
The goal is practical, reliable ML in production: connecting ML capabilities to user-facing functionality through robust backend architecture, data pipelines, and clear implementation documentation.
Role summary
This is not a research or data science role. You will integrate ML models and third-party ML APIs into systems that run in production, then own the reliability, performance, and scalability of ML-adjacent backend components across the Good Inside platform.
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 (examples include LLM providers, recommendation engines, and embeddings services) into production systems
- Build data pipelines and infrastructure for model serving, feature storage, and real-time personalization
- Work closely with product, mobile, and design teams to turn ML capabilities into user-facing features
- Own reliability, performance, and scalability of ML-adjacent backend systems
- Write clean, maintainable, and well-documented code aligned with defined project scope
- Document architectural decisions, implementation details, and handoff materials after project completion
- Provide input on feature scope and sequencing to support timely delivery of project deliverables
Requirements
- 5+ years of professional software engineering experience with strong backend focus
- Experience shipping ML-powered features or products in a production environment
- Working knowledge of ML concepts such as embeddings, classification, recommendation systems, and LLMs (no model training required, but understanding how and when to use them is)
- 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 cross-functional relationship-building ability
- Self-starter approach with strong analytical and problem-solving skills
- Ability to stay organized and deliver results in a fast-paced, changing environment
- Computer Science degree or equivalent
- At least 2 years of experience in house as a ML Engineer
Technologies
Python, Go, Java, TypeScript/Node, OpenAI, Anthropic, ElevenLabs, HuggingFace, AWS SageMaker, AWS, GCP, Azure, vector databases, feature stores, streaming systems
Benefits
- Base salary: $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 experience
- Startup growth experience and excitement about scaling a high-growth startup from the bottom up
- LLM application development experience (prompt engineering, RAG pipelines, conversational AI, or similar) with an understanding of practical shipping challenges
- Infrastructure and DevOps fluency, including CI/CD, monitoring, observability, and production-readiness for ML systems
- Experience with recommendation systems, personalization engines, or content ranking algorithms in a user-facing product
Location: New York, NY (onsite)
Education: Computer Science degree or equivalent
Minimum experience: 5 years
