Senior Engineer: AI/ML Infrastructure & Generative Systems

Overview
We are a team out of MIT incubated by UM6P Foundry reinventing how organizations capture and leverage their institutional knowledge.Our platform transforms fragmented information into a trusted resource that powers faster decisions and long-term innovation. We are now hiring an experienced engineer to lead the build-out of our AI/ML infrastructure and generative systems (with possible path to CTO). This is a hands-on role at the cutting edge of LLM deployment, GPU optimization, and retrieval-augmented generation (RAG). You’ll own core components of the platform and collaborate directly with the founding team to shape the technical roadmap.

In this role you will

• Design, build, and deploy retrieval-augmented generation (RAG) pipelines using LLMs and vector databases.
• Develop secure backend APIs for data ingestion, indexing, and semantic search across enterprise systems (e.g., SharePoint, Teams, SQL).
• Manage GPU-based inference environments optimized for scalability, latency, and cost.
• Implement MLOps best practices for training, fine-tuning, evaluation, and deployment of generative AI models.
• Collaborate with founders on architecture and build-vs-buy decisions to accelerate roadmap.
• Own the full lifecycle from prototype → MVP → production, ensuring security, compliance, and enterprise readiness.
• Support prototyping of lightweight front-end interfaces to showcase platform capabilities.

**This role based in Cambridge, MA**

Required Qualifications

• 3+ years of experience in ML infrastructure, backend engineering, or AI platform development.
• Experience deploying LLMs and generative AI models in production, with fluency across multiple frameworks such as PyTorch, TensorFlow, Hugging Face, and Azure OpenAI.
• Hands-on expertise in LLM post-training, alignment, fine-tuning, and deployment.
• Strong backend development skills in Python (FastAPI, Flask, or Django) and REST/GraphQL APIs.
• Hands-on experience with GPU inference and performance tuning.
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, or FAISS) and semantic search.
• Comfort working in an early-stage startup environment and delivering under ambiguity.

Preferred Qualifications

• Master’s or PhD in Computer Science, ML, or related field.
• Experience fine-tuning and aligning LLMs (RLHF, LoRA, adapters, prompt tuning).
• Experience with knowledge graphs, enterprise knowledge management, or large-scale search systems.
• Familiarity with LLM orchestration frameworks (LangChain, LlamaIndex) or MCP protocol.
• Prior experience as a founding/early engineer at a startup.

Job Type: Full-time

Pay: $110,000.00 - $120,000.00 per year

Benefits:

• Flexible schedule
• Health insurance
• Paid time off

Education:

• Master's (Required)

Experience:

• AI: 5 years (Required)
• ML: 5 years (Required)

Ability to Relocate:

• Cambridge, MA 02142: Relocate before starting work (Required)

Work Location: In person