---
title: 'Research Engineer at SuperAnnotate AI'
canonical: 'https://feeny.ai/job/research-engineer-superannotate-ai-san-francisco-84vwmt7042sg'
type: 'job'
last_seen: '2026-09-09'
---

# Research Engineer at SuperAnnotate AI

- **Company:** SuperAnnotate AI
- **Location:** San Francisco, CA
- **Compensation:** $180k–$250k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-07-20
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.lever.co/superannotate/26b7799a-b68a-47d2-bde1-891fbd7e2e68

## Job description

## About SuperAnnotate

SuperAnnotate helps the world’s leading AI teams build responsible, next-generation models powered by high-quality human data. We’re a fast-growing Series B startup bridging the gap between advanced AI innovation and the data that drives it. Our global network of expert specialists, scalable managed operations, precise talent matching, and full project transparency ensure unmatched data quality at scale. Trusted by innovators like Databricks and ServiceNow - and backed by NVIDIA, Dell Technologies Capital, Databricks Ventures, Cox Enterprises, and Lionel Messi’s Play Time VC - SuperAnnotate is proud to be the top-ranked AI data company on G2 for multiple consecutive years, including 2025.

The Impact You'll Make Our research team is expanding to keep pace with a wave of frontier-facing work: internal research streams, client engagements that require real ML depth, and emerging opportunities at the cutting edge of the field. As a Research Engineer, you'll take a research direction and run with it – finding the right papers, benchmarks, and prior work, reimplementing what's relevant, and building out the process to reproduce and improve on it internally. You'll own initiatives end to end: partnering with strategic project and technical leads to scope the work, building MVPs to validate ideas (including through human annotation and agents), and turning that work into something concrete – a customer dataset, a pilot, an internal dataset that becomes a paper or blog post, or a joint publication with a partner. You won't be handed a fully specified task list; you'll be given a direction and the autonomy to turn it into a research plan. This is a full-time, hybrid position based in San Francisco.

## What You'll Do

- Take a research direction and independently identify supporting resources – papers, benchmarks, blog posts – then implement or reimplement the relevant methods.
- Build and own the process to reproduce prior work internally and identify ways to improve on it.
- Own projects (for example, an RL/agentic environment build for a partner or a novel multimodal benchmark) end to end, including scoping, MVP implementation, and validation.
- Partner with strategic project leads and technical leads to translate ambiguous requirements into a concrete, testable research plan.
- Validate ideas through hands-on implementation, including annotating, evaluating, or sourcing data.
- Turn research directions into tangible outputs – a paid customer dataset, a customer pilot, an internal dataset, or a paper/blog post for publication or conference presentation.
- Bring an ML perspective to new opportunities — assessing technical feasibility of incoming requests and helping shape proposals where research depth is needed.

## What You'll Bring

- MS or PhD in ML, CS, or a related quantitative field – or equivalent demonstrated research experience (publications, significant open-source research work, industry research).
- Real ML depth: you understand how models are trained and evaluated, not just how to call an API. You can read a paper, judge whether its claims hold, and reimplement the method.
- Hands-on experience with at least one of: RL/agentic systems, AI/ML evaluation and benchmarking, or multimodal ML.
- Strong Python and the engineering ability to build and ship your own experiments – eval harnesses, environments, infrastructure – without relying on a platform team.
- High autonomy: you can turn an ambiguous direction into a concrete research plan and notice when something's off before being told.
- Clear technical writing

## Nice To Have

- Publication track record (first-author preferred).
- Experience with agent or multimodal benchmarks (OSWorld, MMMU, WebArena, SWE-bench, or similar) or building RL environments/gyms.
- Familiarity with reward modeling, reward hacking, or verifier/judge reliability.
- Familiarity with synthetic data generation or human-in-the-loop (HITL) workflows.
- Experience with cloud infrastructure and containerized environments.
- A deep RL background specifically.

## Why SuperAnnotate

This is a rare opportunity to work at the intersection of frontier AI research and real production impact. You'll work on projects with frontier labs that move the needle on model performance, with your work feeding directly into the next generation of agent capabilities. You'll have the opportunity to implement projects that actually matter, publish research, and present at conferences – alongside a multidisciplinary, multinational team and collaborate with some of the most prominent labs and AI companies globally.

Only shortlisted candidates will be contacted for an interview!

## Equal Opportunity

We are an equal-opportunity employer and value diversity at our company. At SuperAnnotate diversity means to us making an effort to reflect the many experiences and identities of the outside world, and treating each other with fairness and without bias. Every day we foster an environment where people of all backgrounds not only belong, but excel to succeed as a company and grow together. We offer equal opportunity regardless of sex, sexual orientation, national origin, color, race, age, marital status, disability, gender identity, veterans and more.

## About SuperAnnotate AI

## Company Overview
- **One-liner**: SuperAnnotate provides a data-centric platform and integrated managed services for building, evaluating, and aligning frontier AI models through high-quality human data annotation and reinforcement learning.
- **Entity Type**: Private (Series B, $50M total funding)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2018
- **Founders**: Vahan Petrosyan (CEO & Co-founder), Tigran Petrosyan (Co-founder)

## Core Business
- Primary industry/industries: AI Data Infrastructure, Software Development, Data Annotation & Evaluation
- Target customers: Enterprise AI teams, frontier research labs, and advanced AI model builders (B2B/Enterprise)
- Mission or purpose statement: "Accelerate the pace of AI innovation to create a smarter, safer, and more sustainable world."

## Products & Services
- **Platform**: A feedback-driven annotation and evaluation platform to create and manage training data. Includes tools for building custom annotation UIs (low-code "Builder"), orchestrating CI/CD pipelines, automating data workflows, and fine-tuning AI models.
- **Managed Services**: A global network of thousands of rigorously vetted experts for ethical, scalable managed operations, precise talent matching, and end-to-end project visibility. Powers annotation, evaluation, and reinforcement learning workflows.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: $50M total funding raised (Series B of $36M in Nov 2024, expanded to $50M with a $13.5M investment from Dell Technologies Capital in June 2025). Annual revenue is estimated at $45.5M.
- **Notable Investors/Partners**: NVIDIA, Databricks Ventures, Dell Technologies Capital, Cox Enterprises (via Socium Ventures), Lionel Messi’s Play Time VC, Base10 Partners, Point Nine Capital.
- **Growth Signals**: Named 2025 Databricks Customer Impact Partner of the Year. Workforce of 253 employees (+19.9% YoY). Trusted by Databricks, IBM, and ServiceNow. Rated #1 AI Data Company on G2.

## Competitive Advantages
- **End-to-End Platform + Services**: Combines a purpose-built technology platform with a global network of vetted experts, offering full project visibility and control.
- **Top-Tier Backing & Trust**: Backed by leading AI infrastructure players (NVIDIA, Databricks) and trusted by major enterprise innovators, creating a powerful ecosystem and credibility.
- **Focus on Complex Frontier AI Workflows**: Specifically designed for advanced tasks like evaluation, alignment, and reinforcement learning, not just basic annotation.

## Strategic Focus
- Scaling its global expert network and platform capabilities to meet the exploding demand for high-quality human data to build, evaluate, and align frontier AI models.
- Deepening partnerships within the AI ecosystem (e.g., with NVIDIA, Databricks) to integrate its offerings and expand its enterprise customer base.

## Why Work Here
- **Culture & Values**: Described as a fast-paced environment fostering innovation, professional development, and personal growth. Core values focus on collaboration, ownership, and impact.
- **Team & Global Presence**: A diverse team of 253 people across 48 countries, with offices in San Francisco (HQ), Yerevan, Armenia, and Stockholm, Sweden. Offers a hybrid work model for many roles.
- **Benefits**: Offers health insurance & wellness programs, stock options, growth & development opportunities, and a retirement plan.
- **Engineering & Technical Environment**: A significant portion of the workforce (18%) is in technical roles. The company is building the "backbone of AI," working on cutting-edge problems in data infrastructure for large language models and frontier AI.
- **Hiring Process**: A transparent, structured process: Resume screening → Recruiter screen → Team meet → Skills assessment → Leadership interview. All candidates for a given role go through the same process. They are an equal opportunity employer.

## Sources
1. [superannotate.com](https://www.superannotate.com/company)
2. [superannotate.com](https://www.superannotate.com/careers)
3. [linkedin.com](https://www.linkedin.com/company/superannotate)
4. [cbinsights.com](https://www.cbinsights.com/company/superannotate)
5. [jobs.lever.co](https://jobs.lever.co/superannotate)

## Other roles at SuperAnnotate AI

- [Workforce Experience Associate / Specialist](https://feeny.ai/job/workforce-experience-associate-specialist-superannotate-ai-dhaka-5029ehcrtewd) — Dhaka, Bangladesh
- [Global Account Director](https://feeny.ai/job/global-account-director-superannotate-ai-san-francisco-f341bsz8dz6x) — San Francisco, CA
- [Strategic Projects Lead (Technical)](https://feeny.ai/job/strategic-projects-lead-technical-superannotate-ai-san-francisco-58zdv2bywm55) — San Francisco, CA
- [Test Engineer](https://feeny.ai/job/test-engineer-superannotate-ai-yerevan-yqv663a6c5kw) — Yerevan, Armenia
- [Research Engineer](https://feeny.ai/job/research-engineer-neo4j-london-60zcrspx4hjf) — London, United Kingdom
- [Research Engineer](https://feeny.ai/job/research-engineer-greptile-san-francisco-a4grmc0eancw) — San Francisco, CA
- [Research Engineer](https://feeny.ai/job/research-engineer-tessera-labs-san-jose-2atk17ayc2pm) — San Jose, CA
- [Research Engineer](https://feeny.ai/job/research-engineer-verisign-reston-k0fceehptgcr) — Reston, VA
- [Research Engineer](https://feeny.ai/job/research-engineer-antimetal-hq-new-york-ny-n112cvsmbp0c) — HQ / New York, NY
- [Research Engineer](https://feeny.ai/job/research-engineer-decagon-san-francisco-fm6k4wz5aj59) — San Francisco, CA