Machine Learning Engineer

Raydar; New York (NY); Presencial; USD 175 000 - 350 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Equity

Visa sponsorship

On-site in NYC

Resumo da oferta

Raydar in New York City is seeking an experienced machine learning engineer to own end-to-end projects that bring intelligence into production. You will design multi-agent architectures, run hundreds of experiments, and ship systems that help agents reason and plan.

You should have 4–12 years of experience with LLM-based agent applications, strong Python skills, and a CS/Physics/Math background. This is a full-time, on-site role in Flatiron, NYC.

Qualificações

• 4–12 years of ML engineer experience with end-to-end LLM-based agent apps.
• Experience at startup or top tech company.
• Experience running structured ML experiments and eval infra.
• A CS/Physics/Math degree from a top school.
• A clear communicator who can break complex ideas down.
• Currently located in US or Canada, ideally East Coast.

Responsabilidades

• Design and iterate multi-agent architectures with autonomy boundaries.
• Build evaluation pipelines with tasks, labeling and metrics.
• Instrument stack to detect regressions and drive improvement.
• Engineer context and retrieval: prompt stacks, indexing pipelines, parsing docs.
• Scope projects, write specs and communicate progress within the team.

Conhecimentos

End-to-end ML

LLM agents

Benchmarking

Experimentation

Clear communicator

CS/Physics/Math degree

Formação académica

CS/Physics/Math degree

Ferramentas

Python

LLM/transformer systems

Descrição da oferta de emprego

About the Role

Own end-to-end projects that bring intelligence into production. You will be responsible for systems that help agents reason, plan and evaluate themselves, with full autonomy to plan projects, define success, run experiments and decide when a system is ready to ship. This role suits engineers who want to operate like researchers and builders at once.

What You Will Do

• Design and iterate multi-agent architectures, encoding autonomy boundaries, tool use and fallback behavior that make agents safe and reliable.
• Build scalable offline and online evaluation pipelines that run hundreds of experiments, with golden tasks, labeling strategies and metrics.
• Instrument the stack to detect regressions, track error taxonomies and drive closed-loop improvement.
• Engineer context and retrieval: prompt stacks, indexing pipelines and parsing of messy documents into structured representations.
• Scope projects clearly, write concise specs and communicate progress within your pod.

What We Are Looking For

• Four to twelve years as a machine learning engineer, with end-to-end 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 CS, Physics, Math or related technical degree from a top school. The role is applied rather than research-focused.
• A very clear communicator who can break complex ideas down.
• Currently located in the US or Canada, ideally on the East Coast.

Bonus Points

• Deep Python expertise and LLM or transformer-based systems.
• Interest in the impact of AI on professional services and the economy.

Compensation and Benefits

$175,000-$350,000 base salary plus highly competitive equity, depending on experience. Visa transfers and sponsorship are available.

Location and Work Model

Full-time and on-site five days a week in Flatiron, New York City.