--- title: 'Member of Technical Staff - Research Software Engineer at Reflection' canonical: 'https://feeny.ai/job/member-of-technical-staff-research-software-engineer-reflection-new-york-5v6c5c4y3fvm' type: 'job' last_seen: '2026-10-15' --- # Member of Technical Staff - Research Software Engineer at Reflection - **Company:** Reflection - **Location:** New York, NY - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-03-12 - **Last confirmed live:** 2026-10-15 - **Apply:** https://jobs.ashbyhq.com/reflectionai/bf075674-ad6c-4ab6-aa30-f7c37c59e759 ## Job description ## Our Mission Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all. The Roles Mission Bridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models — from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines. Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility. What This Team Does This team owns and evolves the core infrastructure behind our training systems. We focus on: - Reinforcement learning training infrastructure - Distributed training and inference systems - Experiment infrastructure and reproducibility - Large-scale data pipelines The goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale. ## About the Role You will architect and optimize the core training infrastructure that powers our models. This includes RL training loops, distributed GPU systems, and large-scale data pipelines. You will work closely with researchers to transform new ideas into reliable, scalable training systems. Responsibilities include: - Designing and optimizing large-scale training loops and data pipelines. - Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient. - Building internal tooling for launching, monitoring, and reproducing complex experiments. - Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls). - Translating research prototypes into reusable, production-grade infrastructure. ## What You'll Work With Distributed Training - GPU parallelism (data, tensor, pipeline, expert) - Large-scale distributed training infrastructure - Communication optimization (NCCL, RDMA, GPU interconnects) - FSDP / ZeRO and model sharding Orchestration & Runtime Systems - Ray, Kubernetes, Slurm - Distributed runtimes and async systems - Containerization and sandboxing Frameworks - PyTorch - JAX - Megatron-style training stacks - Triton / custom kernels Data Infrastructure - Large-scale dataset curation pipelines - Deduplication and filtering systems - Tokenization and preprocessing - Distributed data processing frameworks ## About You - You are a strong software engineer who speaks the language of machine learning. - You may not have a PhD, but you know how to implement a research paper. - You have deep experience in at least one of the following: Distributed Training & Inference or Data Infrastructure - You enjoy working at the boundary between: - Machine learning algorithms - Distributed systems - High-performance computing - You care deeply about performance, numerical stability, and reproducibility. - You thrive in high-agency environments and enjoy solving hard technical problems. What We Offer: We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported. - Top-tier compensation: Salary and equity structured to recognize and retain our talent globally. - Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options. - Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance. - Meals: Lunch and dinner are provided in the office daily. - Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys. - Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K. - Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable. - Team building: We have regular off-sites, happy hours, and team celebrations. Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization. Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our [Candidate and Employee Privacy Notice](https://cdn.sanity.io/files/irpbdun9/production/ee08c38bf22bd45a3f3a81f6a7abddb9210726b7.pdf) ## About Reflection ## Company Overview - **One-liner**: Reflection is an AI lab building frontier open-weight models and superhuman coding agents, founded by former researchers from DeepMind, OpenAI, and Anthropic. - **Entity Type**: Private (funding stage: Series B) - **Headquarters**: New York, New York, United States - **Founded**: 2024 (seed round in September 2024) - **Founders**: Misha Laskin (Co-Founder, CEO), Ioannis Alexandros Antonoglou (Co-Founder, President & CTO) ## Core Business - **Primary industry/industries**: Artificial Intelligence (AI research and development), Software Development - **Target customers**: Enterprises, governments, sovereign entities, and developers seeking open, high-performance AI models and autonomous coding agents (B2B, B2G). - **Mission or purpose statement**: "Make intelligence open and accessible to all" – building frontier open-weight models with transparent research and collaborative development. ## Products & Services - **Reflection Open-Weight Models**: Frontier large language models (LLMs) designed for enterprise and sovereign use, offering ownership and control. - **As I/O (Announced 2025)**: A production-ready platform "powered by Reflection" that gives organizations a complete, integrated system for deploying AI agents and workloads. - **Autonomous Coding Agents**: Superhuman coding agents that automate knowledge work performed on a computer (core research focus). ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: **Total Funding** – $2.13 billion across three rounds: - Seed (Sep 2024): $25M (2 investors) - Series A (Mar 2025): $105M (2 investors) - Series B (Sep 2025): $2.0B (12 investors) - **Notable Investors/Partners**: Investor names not publicly listed in available sources; board includes Max Gazor and Raviraj Jain. Partners not disclosed. - **Growth Signals**: - Headcount grew **411.4% YoY** to 126 employees (as of mid-2026). - Active job postings: **80** (up 1,233% YoY). - LinkedIn followers: 21,763 (up 508% YoY). - Offices in New York (HQ), San Francisco, London, Washington D.C., and Toronto. - Talent sourced from Google DeepMind (13), Meta (14), OpenAI (3), and other top labs. ## Competitive Advantages - **Open-weight philosophy**: Differentiates from closed labs like OpenAI and Anthropic by giving enterprises and governments full ownership and control of frontier AI. - **World-class team**: Founders and researchers previously built ChatGPT, Gemini, AlphaGo, and AlphaZero – proven track record in both LLMs and agent systems. - **Massive capital**: $2.1B in funding allows aggressive compute investment and talent acquisition. - **Full-stack AI capability**: From training frontier LLMs to deploying production-grade agent platforms (As I/O). ## Strategic Focus - **Current priorities**: Scaling open-weight models to frontier performance; building autonomous coding agents that automate knowledge work; expanding enterprise and sovereign sales (e.g., "Regional Commercial Lead, Sovereign – Europe" job posting). - **Direction**: Making open intelligence the default for enterprise and government AI adoption, with a strong emphasis on transparency and sovereign control. ## Why Work Here - **Culture highlights**: Mission-driven ("Mission above ego"), high trust, extreme ownership, and collaboration. Values include "Trust through truth" and "One team". - **Remote/hybrid/office policy**: In-office daily with lunch and dinner provided. Offices in New York, San Francisco, London, Washington D.C., and Toronto. Relocation support available. - **Notable perks**: - **22 weeks paid parental leave** for all new parents (including adoptive and surrogate). - Unlimited paid time off (U.S.) / 30 days (U.K.). - Stock options for all employees. - Comprehensive medical, dental, vision, life insurance, and annual wellness allowance. - Visa sponsorship for exceptional talent. - **Engineering culture**: Build from the ground up alongside top researchers and engineers; strong emphasis on research and engineering roles (62 technical employees out of 126). ## Sources 1. [reflection.ai](https://reflection.ai/) 2. [Reflection Careers](https://reflection.ai/careers) 3. [LinkedIn - Reflection](https://www.linkedin.com/company/reflectionai) 4. [The Org - ReflectionAI](https://theorg.com/org/reflectionai) 5. [Ashby Jobs - Reflection](https://jobs.ashbyhq.com/reflectionai) ## Other roles at Reflection - [Member of Technical Staff - Pre-Training Evals Infra](https://feeny.ai/job/member-of-technical-staff-pre-training-evals-infra-reflection-new-york-x1kpfgazqndc) — New York, NY - [Senior Talent Operations Specialist](https://feeny.ai/job/senior-talent-operations-specialist-reflection-san-francisco-7fsnkvmtr29x) — San Francisco, CA - [Compliance Manager](https://feeny.ai/job/compliance-manager-reflection-new-york-f0kdpjdm9bnc) — New York, NY - [GRC Engineer](https://feeny.ai/job/grc-engineer-reflection-new-york-gwe2nxryze7j) — New York, NY - [Member of Technical Staff - Shared Services](https://feeny.ai/job/member-of-technical-staff-shared-services-reflection-new-york-mq910y50mach) — New York, NY - [Member of Technical Staff - Data Platform](https://feeny.ai/job/member-of-technical-staff-data-platform-reflection-new-york-1hvextjd2p17) — New York, NY - [Member of Technical Staff - Engineering Lead, Data Platform](https://feeny.ai/job/member-of-technical-staff-engineering-lead-data-platform-reflection-san-zfyhf0tm3qjj) — San Francisco, CA - [Member of Technical Staff - Engineering Lead, Compute Platform](https://feeny.ai/job/member-of-technical-staff-engineering-lead-compute-platform-reflection-san-tdjzakdf3jz8) — San Francisco, CA - [Member of Technical Staff - Engineering Lead, Applications](https://feeny.ai/job/member-of-technical-staff-engineering-lead-applications-reflection-san-francisco-zzzy3ham34jc) — San Francisco, CA - [MTS, Technology & Security Engineering](https://feeny.ai/job/mts-technology-security-engineering-reflection-new-york-nvmqaaxw2nb9) — New York, NY