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M13 · 2 months ago

Backend ML Engineer at Robyn AI

United States

Full-time

Remote

Senior Level

$150K/yr - $250K/yr

6+ years exp

M13 is building the world’s first emotional intelligence layer for AI through their app Robyn, which serves as an emotionally intelligent companion. The Backend ML Engineer will be responsible for designing and shipping scalable backend systems, integrating machine learning models, and managing cloud infrastructure to support the app's functionalities.

ConsultingFinanceFinancial ServicesVenture Capital

Responsibilities

Backend & Infra Ownership

You'll work and add to our C# / .NET / ASP.NET backend api layer (have experience in this or something similar like Java/Spring and can learn quickly) and progressively add many Python microservices (FastAPI or AWS Lambda) with modular, AI-native architecture in mind to build our intelligence layer. Deploy models and setup some ml training pipelines

Understand dependency injection, Strategy Pattern, inversion of control, and other best practices for code maintainability

Own the full backend surface area — auth, APIs, infra, orchestration — and design all of your features for scale and velocity

Build and maintain REST and GraphQL APIs consumed by our iOS client; low-latency, resilient, and well-instrumented

Architect a microservice-style ML model serving backend deployed via Docker containers or AWS Lambda (SnapStart), backed by async eventing and pub/sub where needed

Own CI/CD, rollback strategies, logging, error handling — the backend is your domain, end-to-end

AI & ML Systems Integration

Architect and manage existing vector DB (PgVector) and potentially add more to power retrieval-augmented generation, evolving memory, and personalization

Build tools and add to our custom memory pipelines tied to user context, embeddings, and interaction history

Integrate and scale inference with OpenAI, Claude, Llama, or other models. Build wrappers, manage caching, fallbacks, and prompt routing logic

Own emotion and sentiment tagging workflows; plug in APIs or run lightweight classifiers in-line

Maintain API orchestration layer with 3rd party model providers (OpenAI, ElevenLabs, etc.)

Cloud Infra, DevOps, and Data Stack

Manage our AWS infrastructure and add to our current stack with new innovate technologies: Lambda, ECS, S3, RDS (Postgres), CloudFront, IAM, Route53 — you’ll be the one making the call on architecture and trade-offs

Be able to use search databases like OpenSearch

Infra-as-code with Terraform. Pipelines through GitHub Actions

Full observability: metrics, structured logging, tracing, alerting — Open Telemetry, Sentry, Grafana, Cloudwatch, etc

Optimize latency across API surface, tune Postgres indexes, add Redis caching layers to many of your services and pub/sub or streaming for near-instantaneous data sync

Set up and secure infra for SOC-2 readiness: access controls, data lifecycle policies, encrypted storage

Personalization & Emotional Intelligence Layer

Design and ship emotion-aware backend systems that update in real time based on user behavior

Implement custom memory engines — user embeddings, experience graphs, emotional scores — and build APIs that adapt over time

Work with product and AI to tune behavior of Robyn based on user feedback, emotion logs, memory history, and interaction loops

All personalization logic

Qualification

C#.NETPythonAWSMicroservicesREST APIsGraphQL APIsDockerTerraformPostgresOpenAI integrationSystems ThinkingEmotional IntelligenceCollaborationProblem Solving

Required

6 - 15 years of experience in backend or full-stack development; building 0-1 products or teams in a startup environment

Experience in C# / .NET / ASP.NET backend api layer or similar like Java/Spring

Experience with Python microservices (FastAPI or AWS Lambda)

Understanding of dependency injection, Strategy Pattern, inversion of control, and other best practices for code maintainability

Experience in building and maintaining REST and GraphQL APIs

Experience in architecting a microservice-style ML model serving backend deployed via Docker containers or AWS Lambda

Experience in managing AWS infrastructure and adding to the current stack with new technologies: Lambda, ECS, S3, RDS (Postgres), CloudFront, IAM, Route53

Experience with search databases like OpenSearch

Experience with Infra-as-code using Terraform

Experience with full observability: metrics, structured logging, tracing, alerting

Experience in optimizing latency across API surface, tuning Postgres indexes, adding Redis caching layers

Experience in setting up and securing infra for SOC-2 readiness

Experience in designing and shipping emotion-aware backend systems

Experience in implementing custom memory engines

Ability to work with product and AI to tune behavior based on user feedback, emotion logs, memory history, and interaction loops

Ability to figure things out quickly and dive in wherever needed