Member of Technical Staff - Applied ML
About The Position
Own end-to-end projects that bring intelligence into production. The role is responsible for systems that help agents reason, plan, and evaluate themselves, with autonomy to plan projects, define success, run experiments, and decide when a system is ready to ship. It is suited to engineers who want to work as both researchers and builders. The company is a Series B AI company founded in 2023, working in a high-stakes, regulated professional domain. Its team is based in New York City. This is a full-time, on-site role five days a week in Flatiron, New York City. The base salary is $175,000–$350,000, depending on experience, plus highly competitive equity. Visa transfers and sponsorship are available.
Requirements
- Four to twelve years of experience as a machine learning engineer.
- End-to-end experience building LLM-based agent applications, including benchmarking, orchestration, and evaluations.
- Experience at a fast-paced startup (Series A to D), a quant or hedge fund, or a top-tier technology company.
- Experience running structured ML experiments and building evaluation infrastructure.
- A degree in Computer Science, Physics, Mathematics, or a related technical field from a top school.
- Clear communication skills and the ability to explain complex ideas.
- Currently located in the US or Canada.
Nice To Haves
- Deep Python expertise and experience with LLM- or transformer-based systems.
- Interest in the impact of AI on professional services and the economy.
- Being located on the East Coast is preferred.
Responsibilities
- Design and iterate multi-agent architectures, including autonomy boundaries, tool use, and fallback behavior to make agents safe and reliable.
- Build scalable offline and online evaluation pipelines for running hundreds of experiments, including golden tasks, labeling strategies, and metrics.
- Instrument the stack to detect regressions, track error taxonomies, and drive closed-loop improvement.
- Engineer context and retrieval, including prompt stacks, indexing pipelines, and parsing messy documents into structured representations.
- Scope projects clearly, write concise specifications, and communicate progress within the pod.
Benefits
- Highly competitive equity.
- Visa transfers and sponsorship are available.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
