What are the responsibilities and job description for the AI Production Engineer position at Acceler8 Talent?
AI Production Engineer
Boston, MA
About the Company
We build applied AI systems for clients across a range of industries. Backed by leading venture investors, we are a small, technically ambitious team focused on turning cutting-edge machine learning into reliable, production-ready products. Our work spans ML system design, autonomous agent infrastructure, and complex data applications. We believe the best AI solutions come from engineers who deeply understand both the technology and the problems they are solving.
About the Role
We are hiring AI Production Engineers to take early-stage AI prototypes and transform them into robust, scalable production systems. This role sits at the intersection of software engineering and applied machine learning, requiring strong debugging skills, system design thinking, and a commitment to code quality.
You will work closely with AI Solutions Architects, refining and hardening AI-generated or experimental systems into software that is tested, documented, and reliable in real-world environments.
What We’re Looking For
We are looking for engineers who combine strong fundamentals with curiosity and craftsmanship:
- A systematic, methodical approach to problem-solving, including clear documentation of reasoning and decisions
- Deep understanding of systems across multiple levels of abstraction, from architecture to implementation details
- Strong debugging skills, with the ability to isolate issues using logs, stack traces, and structured hypothesis testing
- Practical experience with machine learning or deep learning systems, paired with genuine interest in the underlying theory
- High standards for code quality, including clean structure, clear abstractions, and disciplined error handling
- Intellectual curiosity and a habit of continuous learning through reading, building, and experimentation
- Strong communication skills, with the ability to explain technical concepts to both technical and non-technical audiences
- Willingness to mentor others through code reviews, documentation, and knowledge sharing
Requirements
- Proficiency in Python, including the ability to write, read, and maintain production-quality code
- Solid understanding of software engineering best practices (testing, version control, system design)
- Experience working with machine learning or AI-based systems in a production or research setting
- Familiarity with debugging and performance optimization in real-world systems
- Experience with PyTorch or similar ML frameworks is a plus
What You’ll Do
- Build, review, and maintain production-grade AI and ML systems
- Refactor prototypes, including AI-generated code, into reliable and scalable software
- Debug production issues using structured, traditional debugging techniques
- Develop and maintain testing frameworks, CI/CD pipelines, and deployment infrastructure
- Conduct code reviews focused on correctness, structure, and maintainability
- Write technical documentation, including system design decisions and post-mortems
- Mentor teammates through reviews, pairing, and internal knowledge sharing
- Stay current with AI/ML research and evaluate new tools for production use
Keywords: AI engineering, machine learning, ML systems, deep learning, production ML, AI infrastructure, LLMs, generative AI, autonomous agents, model deployment, MLOps, CI/CD, model monitoring, data pipelines, distributed systems, backend engineering, software engineering, Python, PyTorch, debugging, system design, scalable systems, code review, testing frameworks, observability, logging, performance optimization, cloud infrastructure, AWS, GCP, Docker, Kubernetes, API development, microservices, experiment tracking, feature engineering, model evaluation, research translation, technical documentation, code quality, software architecture