Research Engineer
Antimetal provides an autonomous production engineering system that continuously understands, operates, and improves software environments. Its platform uses specialized agents and a live world model to diagnose incidents, fix issues, prevent regressions, and automate operational workflows.
Funding history
Investors
About Antimetal
Antimetal is building an autonomous layer between engineering teams and their production systems. The platform connects to existing observability, infrastructure, deployment, and code tools to create a continuously updated world model of the customer’s environment. Specialized agents provide proactive monitoring, incident triage, operational intelligence, and customizable automation, including root-cause investigation, proposed fixes, pull requests, and approved production workflows. It serves teams operating complex software systems and offers integrations with their existing technology stack.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build intelligent systems for infrastructure management by prototyping new approaches, running experiments, evaluating results, and bringing successful research into production. You will develop evaluation infrastructure, explore AI agent, machine learning, reasoning, retrieval, codebase mapping, and orchestration techniques, and collaborate with platform and product teams to create scalable services.
Requirements
- 4+ years of experience in applied machine learning or research engineering
- Production experience with agentic and LLM systems
- Experience with multi-step reasoning, reinforcement learning, fine-tuning, and orchestration
- Experience bringing prototypes into production
- Knowledge of statistical modeling, probabilistic methods, time-series analysis, and evaluation methodology
- Expertise in an applied machine learning area such as search, statistical modeling, or natural language processing
- Experience building and running end-to-end evaluation pipelines with real-world data
- Proficiency in Python and TypeScript
- Experience with common machine learning libraries and data engineering tools
- Problem-solving skills focused on maintainable and scalable code
Responsibilities
- Run experiments across research areas
- Analyze results and validate successful approaches
- Take successful research approaches into production
- Build live and offline evaluation pipelines
- Create benchmarks and synthetic data
- Develop tooling for measuring progress
- Explore techniques for reasoning, retrieval, codebase mapping, and agent architectures
- Collaborate with platform and product teams
- Integrate capabilities into scalable and reliable services
Benefits
- Equity grants
- Fully covered health insurance
- Fully covered dental insurance
- Fully covered vision insurance
- Retirement benefits
- Unlimited paid time off
- Dinner for late-night work
- Monthly fitness stipend
- Work equipment
- Citi Bike benefits
- Train benefits