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

Machine Learning Engineer