Research Engineer

About SuperAnnotate

SuperAnnotate is a rapidly growing Series B startup dedicated to empowering leading AI teams worldwide with superior human-generated data, enabling the creation of advanced, responsible AI models. With a global community of specialists, streamlined managed operations, precise talent alignment, and transparent project processes, the company ensures exceptional data quality at scale. Esteemed clients include Databricks and ServiceNow, and investors encompass NVIDIA, Dell Technologies Capital, Databricks Ventures, Cox Enterprises, and Play Time VC led by Lionel Messi. SuperAnnotate consistently ranks as the top AI data company on G2, including for the year 2025.

Role Impact

The expanding research team focuses on pioneering initiatives involving internal investigations, client collaborations requiring sophisticated machine learning expertise, and cutting-edge technological advances. As a Research Engineer, you will independently explore research directions by sourcing relevant academic papers, benchmarks, and prior studies, replicating significant works, and developing internal processes to reproduce and refine these methodologies.

Responsibilities

• Independently identify and assimilate supporting research materials to implement or reimplement relevant machine learning methods.
• Design and maintain internal workflows to replicate existing research and discover avenues for enhancements.
• Lead projects from conception to execution, including scoping, building minimum viable products, and validating outcomes, such as creating RL/agentic environments or novel multimodal benchmarks.
• Collaborate with strategic and technical leadership to convert ambiguous goals into detailed, testable research plans.
• Validate research hypotheses through practical implementation, data annotation, evaluation, or data sourcing.
• Deliver concrete outputs from research initiatives, including customer datasets, pilot programs, internal datasets, academic papers, or blog posts.
• Provide machine learning insights to assess the feasibility of new opportunities and assist in shaping proposals requiring deep research expertise.

Qualifications

• MS or PhD in Machine Learning, Computer Science, or a related quantitative discipline, or equivalent research experience demonstrated through publications, open-source contributions, or industry research.
• Strong foundational knowledge of machine learning including model training and evaluation, with the ability to critically analyze and reimplement published methods.
• Hands-on experience in at least one of the following areas: reinforcement learning (RL)/agentic systems, AI/ML evaluation and benchmarking, or multimodal machine learning.
• Proficient in Python with the ability to independently engineer and deploy experiments, including evaluation frameworks and custom environments, without dependence on centralized platform teams.
• High self-direction capable of developing a detailed research plan from broad directions and proactive identification of issues.
• Excellent technical writing and communication skills.

Preferred Skills

• Record of published research articles, preferably as first author.
• Experience with agent or multimodal benchmarks such as OSWorld, MMMU, WebArena, SWE-bench, or similar platforms.
• Understanding of reward modeling, reward exploitation problems, or the reliability of verifiers/judges.
• Knowledge of synthetic data generation or human-in-the-loop workflows.
• Familiarity with cloud infrastructure and containerized environments.
• Specialized background in deep reinforcement learning.

Why Join SuperAnnotate

This position offers the unique chance to engage with frontier AI research that directly influences real-world production systems. Collaborate with leading labs to enhance model functionality and contribute to widely recognized research publications and conferences. Join a diverse, multinational, and multidisciplinary workforce committed to innovation and excellence.

Equal Opportunity Employer

SuperAnnotate is committed to diversity and inclusion, ensuring fairness regardless of gender, sexual orientation, nationality, race, disability or veteran status. The hiring process may utilize artificial intelligence tools for resume and application analysis; however, final hiring decisions are made by human recruiters.

Compensation

Beyond a competitive base salary, employees qualify for an annual bonus distributed quarterly.