AI Engineer
At a glance
Mid-level AI Engineering role at Normal Computing Corporation. New York · full-time · $200,000–$400,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI systems that interpret model designs, technical documents and chip verification materials, then deploy and refine them
- Develop agent-based coding and tool-use workflows using reinforcement learning and research loops with measurable rewards
- Control latency, inconsistent outputs and failures so AI features remain dependable in production
- Connect AI capabilities to the platform with product and engineering teams, while coaching junior engineers
What you bring
- You have delivered AI systems using language models in production, ideally including agentic coding and tool use
- Strong software engineering experience includes distributed systems, job scheduling and production-quality code
- You can build with Python and modern machine-learning frameworks such as PyTorch or Hugging Face
- You have tuned prompts, adapted models and deployed large language models, and can benchmark models, runtimes and hardware
- You can make complex AI ideas clear to both technical and non-technical audiences
Who this fits
This mid-level role suits an engineer who can take AI work from an initial idea through deployment and ongoing improvements, while mentoring junior teammates. The position is hybrid in New York.
From the employer
Normal Computing | Build with Us
Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.
The Role
As an AI Engineer at Normal, you will build production systems that understand AI model architectures, technical documents and chip design & verification collateral like reference models, testbenches, FPGA emulation or analog simulations, and help build autoresearch loops, verifiers and infrastructure to optimize the design process. You'll ship real improvements to our production platform while pushing the boundaries of what's possible in AI for hardware through reinforcement learning, agentic coding, and exceptional software engineering.
What You Will Own
End-to-End Development: Lead AI development from initial concept through production deployment and iteration.
Agentic Systems: Handle multi-modal complexity and explore multi-agent, autoresearch and RL approaches for agentic code generation and tool use, interacting with both physical and simulated rewards.
Production Quality: Design strategies to manage latency, output variance, and graceful error handling at scale.
Platform Integration: Collaborate with product and engineering teams to embed AI capabilities seamlessly into our platform.
Mentorship: Guide junior engineers and establish best practices for AI development.
What Makes You a Great Fit
Previous experience delivering production AI systems involving language models, preferably involving agentic coding workflows & tool use.
Solid software engineering skills with experience in distributed systems, job scheduling and production-grade code
Proficiency in Python and modern ML frameworks (PyTorch, Hugging Face, transformers)
Experience with benchmarking and profiling different ML models, runtime configurations (VLLM/SGLang) and hardware architectures.
Hands-on experience with prompt engineering, fine-tuning, and deploying large language models
Ability to explain complex AI concepts to both technical and non-technical stakeholders
Bonus Points
Experience with hardware design, hardware verification, or EDA tooling
Experience deploying AI systems in mission-critical or high-stakes production environments
Experience with cloud platforms (AWS, GCP, Azure) for large-scale AI infrastructure
Research or applied experience with LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, or program synthesis
Open-source contributions or publications in AI/ML venues
Skill in balancing cutting-edge innovation with production reliability and pragmatism
Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Applicant Privacy Notice.