Senior Machine Learning Engineer, Digital Twin Platform
Develop and deploy production machine learning models for real-time inventory and shelf-stocking intelligence at scale. The role requires 5+ years of production ML experience, strong Python and ML framework skills, cloud and data pipeline expertise, and a bachelor's degree or equivalent experience.
About the job
Responsibilities
- Design, develop, and deploy machine learning models for real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations.
- Own the full machine learning lifecycle, including problem framing, data exploration, model training, evaluation, and production deployment.
- Collaborate with software engineers, computer vision engineers, data scientists, and product leads on technology and product innovation.
- Contribute to the Digital Twin Platform infrastructure, including retail-partner data ingestion and collection of inventory observations for modeling pipelines.
- Help define the technical direction of an expanding modeling practice.
Requirements
- 5+ years of experience developing and deploying machine learning models in production environments.
- Strong proficiency in Python and experience with TensorFlow, PyTorch, or scikit-learn.
- Experience with large-scale data pipelines and structured and unstructured data.
- Experience with cloud infrastructure such as AWS, GCP, or Azure.
- Familiarity with ML platform tooling for model training, versioning, and serving.
- Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.
Nice-to-haves
- Experience with computer vision, inventory forecasting, demand sensing, or spatial/temporal modeling.
- Familiarity with real-time, low-latency, high-throughput ML inference systems.
- Experience independently driving projects from conception through production.
- Exposure to retail, supply chain, or e-commerce domains.
- Experience collaborating with computer vision teams or incorporating vision-based signals into ML systems.
Compensation and Benefits
- ATS-listed base salary range: $201,000–$253,500 USD.
- Role is remote and base pay depends on permanent work location.
- Eligible for a new-hire equity grant and annual refresh grants.
- Competitive compensation and benefits.
Skills
Python, TensorFlow, PyTorch, scikit-learn, AWS, GCP, Azure, Machine Learning, Computer Vision, Data Pipelines, Real-Time Inference, Ml Model Serving, Model Versioning, Inventory Forecasting, Spatial Modeling
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