Job Summary: 

• Be in charge of finding the best deep learning solutions to challenging problems in 3D geometry
• Take ownership of the implementation of state of the art deep learning models
• Architect a rapid development framework for building, training, and evaluating deep learning models
• Join a growing CV team building the core technology underpinning product
• Work with the product and engineering teams to deploy models and pipeline in production and build tools to evaluate performance.
• Design, implement, and evaluate models and software prototypes
• Create and improve deep learning architectures and corresponding software stack (visualization, neural network infrastructure)
• Engage in team collaboration to meet joint research goals
• Train deep learning models
• Solve problems in the field of deep learning
• Develop algorithms in the field of deep learning

Skills on Resume: 

• Deep Learning Solutions (Hard Skills)  
• Model Implementation (Hard Skills)  
• Rapid Development Framework (Hard Skills)  
• Cross-functional Collaboration (Soft Skills)  
• Model Deployment (Hard Skills)  
• Software Prototyping (Hard Skills)  
• Model Training (Hard Skills)  
• Algorithm Development (Hard Skills) 

Job Summary: 

• Investigating innovative machine learning and statistical techniques for health problems
• Liaising closely with scientists, and other deep learning engineers and data scientists, to turn medical problems into data science challenges
• Designing and implementing machine learning pipelines
• Designing, developing and deploying machine learning models into production
• Solving problems such as disease progression analysis in CT scans
• Reporting analyses and insights to non-technical stakeholders and audiences
• Join as the Lead Deep Learning Engineer with the sole aim of using cutting-edge and pioneering techniques to help companies to better improve interaction with users and customers alike. 
• Manage 1 Data Scientist and have responsibility for the companies next generation of products.

Skills on Resume: 

• Machine Learning Investigation (Hard Skills)  
• Collaboration with Scientists (Soft Skills)  
• Pipeline Design (Hard Skills)  
• Model Deployment (Hard Skills)  
• Problem Solving (Hard Skills)  
• Reporting Insights (Soft Skills)  
• Leadership (Soft Skills)  
• Product Development (Hard Skills)  

Job Summary: 

• Apply machine learning techniques to solve customer challenges and optimize deep learning pipelines.
• Expected and encouraged to keep ML and Data Science skills current
• Work with internal and external partners, putting AI solutions into production.
• Spend time working directly with internal and external partners to understand needs, apply data science expertise to ideate and solve complex AI problems.
• Deep learning model selection, optimizing performance of AI models, deployment optimizations, and end-to-end AI solutions architecture.
• Working with customers, also anticipate emerging trends, and work with the product groups to influence product roadmaps.
• Presenting complex ideas to internal and external technical leaders and CxOs.
• Selection and development of models using a variety of techniques and toolsets.
• Program the entire models in Python Tensorow/Keras packages
• Deploy Neural Networks to production using AWS
• Comment code using Sphinx package to produce HTML file guide

Skills on Resume: 

• Machine Learning Application (Hard Skills)  
• Continuous Learning (Soft Skills)  
• AI Solution Implementation (Hard Skills)  
• Customer Collaboration (Soft Skills)  
• Model Optimization (Hard Skills)  
• Trend Anticipation (Soft Skills)  
• Technical Presentation (Soft Skills)  
• Python Programming (Hard Skills)  

Job Summary: 

• Conduct design evaluation and development in order to build and optimize deep learning software frameworks for internal and customer use
• Design, develop and optimize for deep learning training and inference frameworks mapped on customer requirements and internal roadmaps
• Implement various distributed algorithms such as model/data parallel frameworks, parameter servers, dataflow based asynchronous data communication in deep learning frameworks. 
• Algorithm integration in end to end customer use cases
• Profile distributed DL models to identify performance bottlenecks and propose solutions across individual component teams.
• Optimizing code for various computing hardware backends.
• Integration for end customer frameworks
• Debugging multithreaded applications
• Direct customer interaction
• Build strong DL models based on scientific research papers and adapt them to needs
• Work in collaboration with the DL Engineer/Manager and the FS Developer

Skills on Resume:

• Deep Learning Development (Hard Skills)  
• Algorithm Optimization (Hard Skills)  
• Distributed Implementation (Hard Skills)  
• End-to-End Integration (Hard Skills)  
• Performance Profiling (Hard Skills)  
• Hardware Optimization (Hard Skills)  
• Customer Interaction (Soft Skills)  
• Team Collaboration (Soft Skills)  

Job Summary: 

• Apply various Deep learning networks, statistical techniques, explore and experiment on new models through research and various frameworks
• Understand and be able to transform large scale data into a usable form
• Filter data with generalization for use and cross-validate models to ensure the requirements are met
• Recommend an-+d justify the algorithms to implement for the problems at-hand
• Implement libraries, algorithms, and tools for processing Lidar data to push the state-of-the-art in obstacle detection, object tracking, and related perception challenges
• Developing solutions for 3Cs Competitive, Cooperative and Complementing sensor framework projects
• Build perception pipeline fusing Camera, LIDAR, RADAR data for 2D and 3D object detection, scene segmentation, classification, tracking, event classification, and motion predictions
• Training and deploying existing deep learning models onto GPUs for production
• Working on distributed training, model benchmarking/measurement, and model optimization
• Working with Python and PyTorch to train and deploy the models

Skills on Resume: 

• Deep Learning Application (Hard Skills)  
• Data Transformation (Hard Skills)  
• Model Validation (Hard Skills)  
• Algorithm Recommendation (Soft Skills)  
• Lidar Data Processing (Hard Skills)  
• Sensor Fusion (Hard Skills)  
• GPU Model Deployment (Hard Skills)  
• Python and PyTorch Proficiency (Hard Skills)  

Job Summary: 

• Design and implement appropriate ML algorithms and tools according to product requirements
• Full closure of development cycle from the initial idea all the way to seamless integration with existing products
• Work as a team member for optimal achievement of project goals
• Select appropriate datasets and data representation methods
• Extract datasets from existing systems written in C/C++
• Run machine learning tests and experiments on the teams chosen platforms (on cloud & on premise)
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems 
• Extend existing ML libraries and frameworks
• Keep abreast of developments in the AI/ML field

Skills on Resume: 

• Machine Learning Algorithms (Hard Skills)  
• Full Development Cycle Management (Hard Skills)  
• Team Collaboration (Soft Skills)  
• Dataset Selection (Hard Skills)  
• Data Extraction (Hard Skills)  
• Statistical Analysis (Hard Skills)  
• System Training (Hard Skills)  
• AI/ML Knowledge Development (Soft Skills)