What are the responsibilities and job description for the Applied AI Engineer, Early Stage Project, X position at X, The Moonshot Factory?
The Team
We are an early stage geoscience AI team at X with a growing, interdisciplinary portfolio. To prove our path to the moon, we make early contact with the real world through both internal and external partnerships. As a member of the team, you are a self-starter, have a deep passion for problem solving and experimentation and will work on 0-1 AI-based products.
The Role
As a ML Engineer, you’ll be instrumental in translating cutting-edge multi-modal AI research into real-world products. You will harness multi-modal foundation models to drive real-world, high-impact outcomes. Additionally, you’ll contribute significantly to centralized scalable training and eval infrastructure.
How You Will Make 10x Impact
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
We are an early stage geoscience AI team at X with a growing, interdisciplinary portfolio. To prove our path to the moon, we make early contact with the real world through both internal and external partnerships. As a member of the team, you are a self-starter, have a deep passion for problem solving and experimentation and will work on 0-1 AI-based products.
The Role
As a ML Engineer, you’ll be instrumental in translating cutting-edge multi-modal AI research into real-world products. You will harness multi-modal foundation models to drive real-world, high-impact outcomes. Additionally, you’ll contribute significantly to centralized scalable training and eval infrastructure.
How You Will Make 10x Impact
- Act like an owner; be fearless in diving deep, asking questions, proposing solutions, establishing consensus and then making things happen.
- Define ML experiments, perform data reviews, train and test various multimodal ML architectures.
- Extensive use of AI for code tooling.
- Get your hands dirty! Identify, design, and implement a set of experiments and move them to MVPs.
- Have fun, learn from your teammates and teach them as well!
- MS/PhD in CS or equivalent practical experience in ML, and 6 years of professional experience building and releasing production software.
- 3 years of hands-on experience in AI research, scalable model training, evals, and model deployments. Experience with multi-model models is strongly preferred.
- We particularly value experience in early-stage or startup environments, where engineers take ownership and drive product development from the ground up.
- ML Ops experience - setting distributed training and eval pipelines. Hands-on experience building scalable data pipelines and managing ML workflows.
- Substantial experience with machine learning frameworks and libraries, such as PyTorch, Hugging Face, or TensorFlow.
- Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform).
- Experience using AI code generation tools.
- Strong Python proficiency.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Salary : $166,000 - $244,000