Machine Learning Engineer

C2R Ventures; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

C2R Ventures in NYC is seeking a Senior ML Engineer to design and implement internal AI-native tools across the firm. You will work with research, investment, compliance and operations to identify automation opportunities and deliver high-leverage tools.

Responsibilities include building on-prem AI tools, designing orchestration components, vector search and retrieval-augmented generation, and secure integration with internal systems and external LLM APIs.

Qualifications

• Strong background in backend or full-stack engineering with ML exposure.
• Experience designing secure, low-latency workflows across data boundaries.
• Familiarity with on-prem infrastructure and AI tooling.

Responsibilities

• Build internal AI tools and automation workflows within on-prem datasets and infrastructure.
• Design components for orchestration, vector search, and retrieval-augmented generation.
• Interface with external LLM APIs through secure endpoints; manage prompts and responses.
• Develop libraries and APIs to support reusable patterns across user-facing tools.

Skills

Backend development

ML tooling familiarity

Security-conscious design

Education

BS/MS/PhD in CS/OR or similar

Tools

Docker

Kubernetes

HAProxy

Logging/Monitoring systems

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.

Responsibilities

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

Qualifications

• BS/MS/PhD in Computer Science, Operations Research, or similar field
• 5+ years’ experience in backend or full-stack engineering, with recent exposure to ML and AI tooling
• Familiarity with standard infra tools (Docker, Kubernetes, HAProxy, logging/metrics systems
• Experience designing secure, low-latency workflows across data boundaries (e.g., using secure middle layers, caching, or pseudonymization