Machine Learning Engineer designing and implementing AI systems focused on Japanese language challenges at Woven by Toyota. Involves technical R&D, system design, and collaboration with cross - functional teams.
About the role
- Senior Software Engineer developing machine learning geospatial products for Planet. Collaborating with engineers and scientists on innovative remote sensing analytics.
Responsibilities
- End-to-end model development & maintenance: Develop new algorithms or methods, implement and test them rigorously, and integrate them into production pipelines. Contribute to their ongoing maintenance and iteratively improve them.
- Advancing geospatial analytics: Innovate on computer vision, time series, and other ML techniques to uncover new insights from satellite and aerial data
- Cross-functional collaboration: Partner with product managers, data scientists, and engineers to define requirements, validate model outputs, and refine algorithms in iterative cycles
- Collaborating with adjacent ML and software engineering teams to ensure seamless integration of ML pre-processing and inference steps, defining best practices for efficient deployment and maintenance of geospatial models
Requirements
- 6+ years of relevant experience of which 5+ years of experience is in machine learning
- Bachelor’s degree in Computer Science or similar
- Deep familiarity with time series methods, computer vision, and embeddings; able to implement, train, and optimize neural networks
- Data handling & preprocessing: Experience wrangling large datasets, ideally with geospatial libraries, combined with frameworks like PyTorch/TF for model development and training
- Ability to experiment with model architectures, and derive data-driven insights to iteratively improve performance and accuracy using an analytical mindset
- ML engineering experience: Comfortable writing clean, modular Python code and applying software development best practices (Git, testing, CI/CD)
- Hands-on production expertise: Experience deploying models (via Docker, Kubernetes, or similar) and understand best practices for monitoring and maintaining them at scale
- AWS or GCP experience
- Excellent communication skills, capable of explaining technical topics to diverse audiences.
Benefits
- Comprehensive Medical, Dental, and Vision plans
- Health Savings Account (HSA) with a company contribution
- Generous Paid Time Off in addition to holidays and company-wide days off
- 16 Weeks of Paid Parental Leave
- Wellness Program and Employee Assistance Program (EAP)
- Home Office Reimbursement
- Monthly Phone and Internet Reimbursement
- Tuition Reimbursement and access to LinkedIn Learning
- Equity
- Commuter Benefits (if local to an office)
- Volunteering Paid Time Off
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