Enterprise AI Engineer: LLMs, Agents & Systems

Boson AI; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Boson AI is seeking a skilled Machine Learning Engineer to join our enterprise team. You will develop and deploy AI solutions, integrating language, vision, and voice models, and build multi-step pipelines with LLMs and agents, in collaboration with researchers and engineers.

The role emphasizes quality, reliability, and secure deployments in enterprise environments, with responsibilities spanning evaluation, fine-tuning, and scalable platform integration to empower clients with autonomous,

Qualifications

• Bachelor’s or Master’s degree in CS/ML or equivalent practical experience.
• Strong GitHub contributions in relevant ML projects.
• Experience with large language or multimodal models and their applications.
• Experience implementing and working with search systems.
• Attention to detail with emphasis on quality, reliability, and security.
• Proficiency in Python, Rust, TypeScript or Go and ML frameworks (PyTorch/JAX).
• Ability to design or orchestrate multi-model pipelines for task automation.

Responsibilities

• Deliver end-to-end ML solutions meeting customer needs and build LLM-powered software.
• Benchmark models and help write evaluations for customers.
• Develop and deploy modern search systems (RAG, DeepSearch) for grounding knowledge.
• Implement and optimize fine-tuning and alignment of large models on domain data.
• Ensure quality, reliability, security, and scalability of models and agentic systems.
• Integrate AI components into a scalable enterprise platform.

Skills

LLM experience

GitHub contributions

Multimodal models

Search systems

Python

Rust

TypeScript

Go

Model orchestration

Education

Bachelor’s or Master’s in CS/ML

Tools

PyTorch

JAX

Job description

Boson AI is seeking a skilled Machine Learning Engineer to join our enterprise team. You will develop and deploy AI solutions, integrating language, vision, and voice models, and build multi-step pipelines with LLMs and agents, in collaboration with researchers and engineers.

The role emphasizes quality, reliability, and secure deployments in enterprise environments, with responsibilities spanning evaluation, fine-tuning, and scalable platform integration to empower clients with autonomous,