Machine Learning Engineer

C2R Ventures; New York (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

C2R Ventures in NYC seeks a Senior ML Engineer to design and implement internal AI-native tools across the firm. You’ll work with researchers, investment, compliance, and operations to identify automation opportunities and deliver robust, high-leverage tools.

You will build internal AI tools operating on on-prem data, design orchestration components, and integrate with external LLM APIs via secure endpoints, while ensuring low latency and strong security across data boundaries.

Qualifications

• Requires advanced degree in CS or related field.
• 5+ years in backend or full-stack with ML exposure.
• Experience with standard infra tools (Docker, Kubernetes, HAProxy).
• Design secure, low-latency workflows across data boundaries.

Responsibilities

• Build internal AI tools and automation workflows on on-prem datasets and infrastructure.
• Design components for orchestration, vector search, and retrieval-augmented generation (RAG).
• Interface with external LLM APIs (e.g., OpenAI, Anthropic) via secure endpoints; manage prompts.
• Develop libraries and APIs to support reusable patterns across user-facing tools.

Skills

ML tooling

Backend development

Full-stack engineering

Security & data governance

Education

BS/MS/PhD in CS

Tools

Docker

Kubernetes

HAProxy

Logging/metrics

Job description

Multi-strategy investment firm in NYC is looking for a Senior ML Engineer to design and implement internal AI-native tools across the firm.

You’ll work closely with users across research, investment, compliance, and operations to identify automation opportunities and deliver robust, high-leverage tools

Responsibilitie

• s Build internal AI tools and automation workflows that operate within on-prem datasets and infrastructur
• e.Design and implement components for orchestration, vector search, and retrieval-augmented generation (RAG) that integrate with internal system
• s.Interface with external LLM APIs (e.g., OpenAI, Anthropic) via secure, controlled endpoints; manage tokenization, prompts, and response
• s.Develop libraries and APIs to support consistent, reusable patterns across user-facing tool

Qualificati

• onsBS/MS/PhD in Computer Science, Operations Research, or similar fiel
• ds.5+ years’ experience in backend or full-stack engineering, with recent exposure to ML and AI tooli
• ls.Familiarity with standard infra tools (Docker, Kubernetes, HAProxy, logging/metrics system
• s).Experience designing secure, low-latency workflows across data boundaries (e.g., using secure middle layers, caching, or pseudonymizatio