Machine Learning Engineer - Enterprise

About the company

Boson AI is focused on creating enterprise-grade AI systems that push beyond standard automation. The team is centered on advanced research in large language models and agentic systems, with the goal of solving difficult business problems and delivering practical value through dependable, high-quality products that fit naturally into enterprise workflows.

About the role

The company is hiring a detail-focused Machine Learning Engineer for its enterprise team. In this position, you will help create and launch advanced AI solutions by combining language, voice, and vision models, applying fine-tuning methods, building workflows and platforms, and developing agentic systems that can complete complex tasks with limited supervision. The work calls for strong model understanding, careful implementation, and a strong emphasis on reliability in enterprise settings.

What you will do

• Build complete solutions for customers by identifying user problems, defining product requirements, and developing software powered by LLMs.
• Create model benchmarks and evaluation workflows to uncover weaknesses and measure performance for customer use cases.
• Design and ship modern search systems such as RAG and DeepSearch to improve grounding, retrieval, and use of organization-specific knowledge.
• Apply fine-tuning and alignment techniques to adapt large models to domain data.
• Maintain strong standards for quality, dependability, security, and scalability in AI and agentic systems, with ongoing monitoring in enterprise environments.
• Connect multiple AI components into a larger, scalable platform.

What you need

• A bachelor's or master's degree in Computer Science, Machine Learning, Artificial Intelligence, or another quantitative discipline, or equivalent hands-on experience.
• A strong GitHub portfolio; applicants are expected to include their GitHub profile in the application.
• Practical experience with large language models or multimodal models and their real-world applications.
• Experience building and working with search systems.
• A consistent focus on precision, reliability, and security in technical work.
• Programming ability in languages such as Python, Rust, TypeScript, or Go, along with familiarity with ML frameworks such as PyTorch or JAX.
• Experience designing, chaining, or orchestrating multiple models into multi-step workflows for automation.

Bonus experience

• Hands-on work on agentic AI products or systems.
• Exposure to AWS, GCP, Azure, or MLOps practices.
• Knowledge of distributed training and inference methods.
• Experience with system design, APIs, and scalable infrastructure for deploying and operating AI models or agentic systems.
• Understanding of enterprise integration patterns and data security considerations.
• Working knowledge of HTTP and real-time communication protocols such as WebRTC for voice AI.
• Strong problem-solving ability.
• Comfort working independently and driving projects in a fast-moving environment.

Data and hiring process notice

The employer may use AI-based tools to assist with parts of recruitment, including resume review, application analysis, response assessment, and spotting possible inconsistencies or verification signals in application materials. These tools support the recruiting team and do not replace human review. Final hiring decisions are made by people. If you want more information about how your data is handled, you can contact the company.