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Applied AI Research Engineer

1 day, 21 hours ago
India
Full-time
Mid Level
AI Research Scientist
Software Development
Computer Vision Generative AI Reinforcement Learning
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Appen

Appen

Appen is a global leader in providing high-quality data management services for AI development. With over 1 million crowd workers, Appen supports the world's top technology companies in enhancing their products and services. The company offers a divers...

IT Services
1K-5K
Founded 1996
$59M raised
View All Jobs 8

Description

  • Build reinforcement learning and agent environments, including task specifications, scoring, and evaluation.
  • Develop benchmarks and evaluation harnesses for model and data accuracy, robustness, safety, latency, and cost.
  • Build LLM pipelines and agentic systems for research, evaluation, and customer trials.
  • Run fine-tuning, adapter, and other model experiments to assess how data and methods affect model behavior.
  • Deploy local or self-hosted models for evaluation, inference, and automation workflows.
  • Document experiments, configurations, data, results, and limitations for reproducibility.
  • Collaborate with the GenAI Research team and cross-functional stakeholders to create reusable customer-engagement assets.

Requirements

  • Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related technical field.
  • 3+ years of professional engineering or relevant industry experience in AI/ML or software engineering.
  • Strong software engineering skills and experience building reliable, maintainable AI systems.
  • Hands-on experience with agentic systems, reinforcement learning environments, LLM pipelines, or similar AI systems.
  • Experience building evaluation harnesses, benchmarks, or model testing pipelines.
  • Ability to work independently and quickly turn research questions into working solutions.
  • Strong understanding of experimentation, reproducibility, and technical documentation.
  • Experience developing synthetic data generation systems or datasets (preferred).
  • Published research papers, benchmarks, or other technical research experience (preferred).
  • Experience with SWE-bench, local inference, open-weight models, or self-hosted model environments (preferred).

Benefits

  • Flexible ways of working supported by team tools and resources.
  • Professional development and opportunities to build technical capabilities.
  • Collaborative culture focused on innovation, accountability, curiosity, and high-quality AI solutions.
  • Opportunity to work on complex AI challenges across industries and geographies.

Interested in this position?

Apply directly on the company website

Apply Now

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