Applied AI Research Engineer
Job description
An Applied Research Engineer role at Appen focused on building practical AI research assets, including reinforcement learning and agent environments, benchmarks, and LLM pipelines, to support Frontier lab initiatives and customer engagements.
At a glance
- Work mode
- Remote
What you'll do
- Build reinforcement learning and agent environments for real customer and Frontier lab use cases, including task specifications, scoring, and evaluation.
- Develop benchmarks and evaluation harnesses to measure model and data quality across areas such as accuracy, robustness, safety, latency, and cost.
- Build LLM pipelines and agentic systems that support research, evaluation, and customer trials.
- Run fine-tuning, adapter, and other model experiments to evaluate how data and methods influence model behavior.
- Deploy local or self-hosted models for evaluation, inference, and automation workflows.
- Document experiments, configurations, data, results, and known limitations so other engineers can reproduce and build on your work.
- Partner with the GenAI Research team and cross-functional stakeholders to turn technical work into reusable assets for customer engagements.
What we're looking for
- 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 building agentic systems, reinforcement learning environments, LLM pipelines, or similar AI systems.
- Experience building evaluation harnesses, benchmarks, or model testing pipelines.
- Ability to work independently on technical problems and move quickly from an idea or research question to a working solution.
- Strong understanding of experimentation, reproducibility, and technical documentation.
Nice to have
- Developed synthetic data generation systems or datasets.
- Published research papers, benchmarks, or other technical research.
- Worked with SWE-bench or similar software engineering evaluation environments.
- Built or deployed local inference, open-weight models, or self-hosted model environments.
Your team
GenAI Research team
The role partners closely with the GenAI Research team and cross-functional stakeholders.
Benefits
- Culture of innovation, collaboration, and excellence.
- Work on complex challenges that shape the future of AI across industries and geographies.
- Flexibility to deliver in a way that works for you and your team.
- Tools, resources, and development opportunities to continue to build your capability over time.
Apply
About Appen
A leader in AI training data for over 30 years
Appen specialises in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Its AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.
Key facts
- more than 1 million contributors in over 200 countries
- AI training data
- Has been a leader in AI training data for over 30 years.
- Specialises in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition.
- AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries.
- Supports model pre training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.
What they value
- Curiosity
- Accountability
- Commitment to delivering the highest quality AI solutions
- Innovation
- Collaboration
- Excellence
- Humility over ego