Senior Applied Scientist - Graph Optimization & Trace Alignment
EUR 61K-86K (estimate) Senior-level Full Time
Tasks
- Align filter and aggregate crowd sourced vehicle traces
- Cluster traces and reject outliers
- Collaborate with cross functional teams to integrate map processing pipelines
- Deploy solutions using Docker on cloud platforms
- Design scalable algorithms for vehicle trace map matching
- Evaluate model and algorithm performance and iterate on failure cases
- Extract lane centerlines and infer lane connectivity
- Formulate and solve optimization problems for lane graph construction
- Implement robust production ready scalable algorithms
- Integrate deterministic and learned methods in pipelines
- Optimize pose graphs and factor graphs
- Perform drift correction at fleet scale
Perks/Benefits
- DevDays events
- Enhanced parental leave
- Extra birthday day off
- Hackathon participation
- Monthly allowance
- Paid access to e-learning resources
- Paid leave for learning days
- Paid leave to care for loved ones
- Personal development budget
- Setup budget
- Volunteer leave
- Work flexibility hybrid office and home
- Work from home country and abroad
Skills/Tech-stack
Azure | C plus plus | Combinatorial Optimization | Databricks | Deep learning | Docker | Factor Graphs | Geospatial deep learning | Graph Neural Networks | Graph optimization | Integer linear programming | Kalman Filters | Linear Algebra | Linear Programming | Machine Learning | Map-matching | Maximum a posteriori | Maximum a posteriori estimation | Neural Networks | Non-Linear | Non-linear programming | Outlier Rejection | Particle filters | Pose graph | Probabilistic state estimation | Python | Robotics | SLAM | Sensor fusion | State Estimation | Trace clustering | Trajectory alignment | Transformer Models
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Cities
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