AI/ML Engineer
Indexed description
About Us
We’re a fast-moving AI startup building the world’s first Warm-Intro Engine for the startup ecosystem.
Our platform blends:
- Large language models
- Graph-based intelligence (Trust Graph)
- Semantic search + vector embeddings
- Multi-agent workflows
to automate warm introductions, opportunity discovery, and relationship management at scale.
We already have early users from top VC firms and top tech companies, and we’re assembling a small, world-class engineering group to build the core intelligence layer powering Gemphere.
If you want to own major systems from day one and help define a new category of networking AI, this is for you.
Responsibilities
AI & Machine Learning
- Build LLM-driven workflows and multi-step agents
- Implement embedding pipelines, vector search, semantic retrieval
- Develop ranking, scoring, and prediction models
- Work with graph-based data (trust, affinity, relationships)
- Build automated evaluation + monitoring systems
Backend & Architecture
- Design and deploy production AI services (FastAPI or similar)
- Build scalable API endpoints around ML logic
- Work with PostgreSQL, Redis, vector DBs, and graph DBs
- Optimize inference latency via batching, caching, and efficient serving
- Deploy containerized workloads on AWS/GCP
Integrations & Systems
- Build pipelines for email/calendar/contact integrations
- Implement identity resolution and context extraction across sources
- Collaborate closely with backend + mobile engineers
Required Skills
- Expert Python (production-level)
- PyTorch or TensorFlow
- Strong experience with LLM orchestration
- Embeddings, vector search, semantic retrieval
- Ranking/recommendation/prediction models
- Graph ML experience (PyTorch Geometric, DGL, etc.)
- Neo4j / TigerGraph or graph-extended Postgres
- FastAPI or similar frameworks
- PostgreSQL + Redis
- Docker + AWS/GCP
Nice-to-Have
- Gmail/Outlook APIs, Calendar APIs
- Experience with workflow automation or multi-agent systems
- Event-driven systems (Kafka, PubSub)
Ideal Candidate
- Has shipped AI systems end-to-end
- Strong fundamentals in ML + distributed systems
- Comfortable owning large parts of the stack
- Thrives in fast-paced, founder-led environments
- Based in Turkey and comfortable with remote US collaboration
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