Machine Learning Engineer
Build and deploy reinforcement learning models to autonomously control mineral refining facilities, optimizing recovery rates, energy use, and uptime in real operating plants.
Research Engineer, Asta
Research Engineer builds ML infrastructure and agentic systems to accelerate scientific discovery in biology, neuroscience, and more. Requires 2+ years experience with Python, PyTorch/JAX/TF, cloud resources, and deep learning for LLM/agent research at Ai2.
119k – 178kSeattle, WAML EngineeringOnsite2+ YOE
About the role
Responsibilities
- Building infrastructure to facilitate the next generation of LLM and agentic research.
- Creating AI tools to facilitate scientific discovery in domains such as biology, cancer research, neuroscience, social science, etc.
- Designing, building, and training machine learning or language models for agentic workflows.
- Bridging the gap between cutting-edge research and a widely adopted product.
- Bringing software engineering best practices to a research environment.
- Supporting and collaborating with an open-source community.
- Releasing contributions as open source software, model releases, additions to Ai2’s public API and open research datasets, and technical reports.
Requirements
- Bachelor’s degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP, or related field, or equivalent experience.
- 2+ years building agentic infrastructure that handles tools, skills, and other artifacts.
- 2+ years building infrastructure for data preprocessing/transformation and machine learning model training, evaluation, inference, and deployment.
- Knowledge of modern deep learning, natural language processing, and reinforcement learning techniques.
- Strong software engineering skills, particularly building performant systems and debugging.
- Experience with Python and PyTorch/Jax/TensorFlow, agentic frameworks (e.g., MCP).
- Familiarity with cloud compute resources (GCP, AWS, Modal) and containerization (Docker).
Nice-to-Haves
- Advanced degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP or related fields.
- Contributions to open-source ML or research libraries (e.g., spaCy, AllenNLP, transformers, langchain).
- Experience operating at scale in production settings.
- Experience in HPC settings.
Compensation
Base salary range: $118,800 - $178,200, plus generous bonus plans.
Skills
PythonPyTorchJAXTensorFlowMachine LearningNatural Language ProcessingReinforcement LearningDockerGCPAWSAgentic Frameworks
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