Machine Learning Engineer

Good Inside is hiring a Machine Learning Engineer (not a research/data science role) to build production backend services and APIs for ML-driven product features.

Responsibilities

• Design, build, and maintain backend services and APIs powering ML-driven features across the Good Inside platform
• Integrate and orchestrate ML models and third-party ML APIs (including LLM providers, recommendation engines, and embeddings services) into production systems
• Create data pipelines and supporting 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 experiences
• Ensure reliability, performance, and scalability for ML-adjacent backend systems
• Write clean, maintainable, well-documented code aligned to defined project scope
• Document architectural decisions, implementation details, and handoff materials when projects are completed
• Provide input on feature scope and sequencing to support timely delivery of project outcomes

Requirements

• 5+ years of professional software engineering experience, with a strong focus 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, but understanding model behavior and use cases is)
• Hands-on experience integrating ML APIs and services (examples listed: 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 data stores and pipelines for ML workloads (examples listed: vector databases, feature stores, streaming systems)
• Excellent interpersonal, verbal, and written communication skills
• Strong collaboration abilities and cross-functional relationship-building
• Self-starter with analytical and problem-solving skills
• Ability to stay organized and deliver in a fast-paced, changing environment
• Computer Science degree or equivalent
• At least 2 years of experience in house as an 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, including scaling in a high-growth environment
• LLM application development experience (examples listed: prompt engineering, RAG pipelines, conversational AI, or similar)
• 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

Experience: 5+ years professional software engineering; at least 2 years in house as an ML Engineer

Compensation: $205k - $235k base salary per year