Member of Technical Staff

Member of Technical Staff Compensation Base salary up to $600,000 + annual cash bonus + long-term incentive + signing bonus Location New York City (4 days onsite) - full relocation included Company Summary A high-performance AI research and engineering lab backed operating with direct accountability for real-world outcomes. Introduction This team is building a fully autonomous decision-making platform designed to operate in complex, high-stakes environments. By combining large-scale predictive systems on structured data with advanced pretrained reasoning models, they tackle problems where performance, reliability, and real-world impact matter. The group operates at the intersection of research and production running large distributed experiments, pushing infrastructure boundaries, and translating cutting-edge ideas into systems that drive decisions at scale. Role Summary As a Member of Technical Staff, you’ll work at the core of a small, elite team of scientists and engineers developing next-generation ML systems. This is a hands-on, high-ownership role where you’ll take ambiguous problems from concept to production, shaping both modeling approaches and the infrastructure that supports them. Your work will directly influence systems deployed in dynamic, real-world environments. What You’ll Do
Prototype novel modeling approaches alongside scientists
Design and implement scalable training pipelines for large-scale ML workloads
Own systems end-to-end across data, training, evaluation, deployment, and monitoring
Build and evolve ML infrastructure (experiment tracking, model registry, feature pipelines, deployment workflows)
Optimize training and inference for latency, memory efficiency, and throughput
Diagnose model failures under distribution shift and improve robustness
Collaborate in small, high-trust teams with direct accountability for outcomes What You’ll Bring
Strong computer science, engineering, or quantitative background (top-tier academic or equivalent practical experience)
Experience at leading technology companies, high-growth startups, research labs, or quantitative environments
Track record of turning ambiguous problems into production systems
Strong software engineering skills in Python and/or C++
Experience deploying ML systems in real-world production environments
Comfort working across classical ML and deep learning approaches
Hands-on experience with distributed training and large-scale data processing
Ability to reason about evaluation, calibration, and model robustness
Clear communication and strong ownership mindset Tech Stack
Python, C++
PyTorch or similar deep learning frameworks
Distributed systems (Ray, Spark, Kubernetes)
Large-scale data processing and training infrastructure
Real-time or low-latency model serving
Experimentation and model lifecycle tooling Why Join?
Direct ownership of systems operating in real-world, high-impact environments
Tight collaboration between research and engineering
Small, elite team with meaningful technical influence
Performance-aligned compensation and long-term upside
Opportunities to push beyond standard tooling and shape next-generation ML infrastructure About People In AI People In AI connects exceptional talent with the world’s most ambitious AI organizations. We partner with pioneering teams across research, engineering, and applied AI to build the technologies shaping the future. Our approach is thoughtful, discreet, and deeply aligned with long-term impact—for both clients and candidates.