• Define and deliver a technology and data product roadmap of internal machine learning systems automating the investment world.
• Work across the full life cycle from data sourcing, gathering, and processing to deliver deep learning models that predict the outcome of potential investment deals. 
• Build DNN models from the state of data collection and processing to the training of models
• Model performance analysis
• Understand where are the caveats of the current processes and improve it
• Deployment of models in a real time environment
• Co-Ownership of an entire Deep Learning (DL) project(s).
• Working with Executive and Product leadership to evolve and define roadmap.
• Identifying what kind of data and how much data to generate to get desired results.
• Adding to Blaize AI Studio's state-of-the-art (SOTA) toolbox.

Skills: Technology Product Roadmap, Data Processing and Sourcing, Deep Learning Model Development, Model Performance Analysis, Process Improvement, Real-Time Model Deployment, Project Co-Ownership, Data Requirements Identification.

• Assist in critical aspects of the product development lifecycle, including product requirement definition, design, implementation, and verification/validation.
• Developing, training, and deploying deep learning models.
• Participate in concurrent engineering teams to define workflow, requirements, and design.
• Provide input to the project schedule and report status against schedule.
• Research, design and prototype new models and approaches based on deep learning, machine learning, and statistical analysis
• Conduct cutting edge R&D in machine learning applications
• Develop proof-of-concept systems to demonstrate advanced performance
• Collaborate with cross-functional teams to design and prototype new features
• Using small datasets to generate impressive results.
• Relentlessly staying on top of the state of the art in computer vision and related areas.

Skills: Product Development Lifecycle, Deep Learning Model Deployment, Concurrent Engineering Participation, Project Scheduling, R&D in Machine Learning, Proof-of-Concept Development, Cross-Functional Collaboration, Computer Vision Expertise.

• Qualification, setup and release of various Intel Optimized Deep Learning software on CPU and GPU
• Automation of existing and new validation activities and inspection systems. 
• Monitoring functionality and performance and quickly triage problems. 
• Evaluate, measure and analyze the Out-of-box functionality and performance of Deep Learning SW products on Intel and competitive platforms. 
• Working with cross functional teams to implement innovative solutions to internal and external customers. 
• Updating and maintaining documentation for performance measurement per engineering changes.
• Work with internal groups to understand and clearly define requirements for a particular tool or feature
• Design and implement tools and features. 
• Validate them at both unit test level as well as at end-to-end network-level. 
• Closely follow-up to ensure these tools/features are used by customers/users, review feedback, iterate and improve the tools

Skills: Deep Learning Software Optimization, Automation of Validation Activities, Performance Monitoring, Functionality Evaluation, Cross-Functional Collaboration, Documentation Management, Requirements Definition, Tool Design and Implementation.

• Working directly with the Founder & CEO (who is leading the artificial intelligence team, both as a manager and as an individual contributor) and other Machine Learning Engineers
• Bridge this gap and build a product that is able to generate high quality, factually relevant and interesting content about any keyword that a user inputs.
• Involve training new models and making improvements to existing ones. 
• Constantly ingesting research papers, finding and implementing ways to take what is cutting edge, and writing production code to apply it to goals. 
• Analyzing where current methods are falling short and devising and implementing ways to improve and iterate.
• Developing new algorithms utilizing a variety of computer vision, deep learning and machine learning techniques.
• Work with teams from across the business to analyse multiple datasets and implement the findings across the group.
• Keep up to date with research and the latest developments in the industry and tools/ algorithms being developed or released.
• Building the vision systems that will ultimately be used in the sensors for Calibration, Normalisation and Detection.

Skills: AI And Machine Learning, Product Development, Model Training, Research Analysis, Algorithm Development, Cross-Team Collaboration, Industry Trend Awareness, Computer Vision Techniques.

• Work on the next-gen state-of-the-art 3D reconstruction, measurement extraction, and size recommendation pipelines
• Run hundreds of experiments and sweeps to discover and select the most promising models
• Structure, process, and prepare datasets, build automated ETL processes for AI models
• Train, optimize, and deploy Deep Learning pipelines on Google Cloud, AWS, and on-premise
• Read state-of-the-art Deep Learning papers, implement and test innovative ideas to improve models
• Work with continuously and fast-growing rich data from fashion apparel products, user interactions, and various state-of-the-art hardware 3D scanners
• Assist in managing continuous data collection process
• Build the DL models that work with audio signals and NLP data
• Researching the architectures that fit the demands (prevent deterioration, increase recall, increase accuracy)
• Monitor and evaluate the performance of the models

Skills: 3D Reconstruction Development, Experimentation and Model Selection, Dataset Preparation, Deep Learning Pipeline Deployment, State-of-the-art Implementation, Data Collection Management, Audio and NLP Model Development, Performance Monitoring and Evaluation

• Contribute to open-source medical image deep learning projects: MONAI and beyond.
• Develop SDKs for NVIDIA customers to develop vertical specific AI solutions.
• Develop solutions to improve the productivity of AI researchers and engineers. 
• Learn the latest technology in deep learning, medical imaging, and GPU.
• Thoroughly studying various Deep Learning compression techniques
• Implementing existing network compression algorithms (pruning, matrix factorization, etc.)
• Developing new network compression algorithms to further accelerate Deep Learning algorithms on accelerator
• Help develop software infrastructure to characterize and analyze a broad range Deep Learning applications
• Classify key workloads based on share of data center cycles, and work with experienced performance engineers to identify ways to improve efficiency.
• Work with experts to help develop analysis and profiling tools in Python, bash and C++ to measure key performance metrics of DL workloads running on Nvidia systems.

Skills: Open-source Contribution, SDK Development, AI Productivity Improvement, Deep Learning Technology Learning, Compression Techniques Analysis, Network Compression Implementation, Software Infrastructure Development, Performance Analysis and Profiling

• Work with team to define application requirements and deliverables
• Define and delegate annotation process for various machine learning tasks
• Innovate new deep learning methods to solve specific clinical problems
• Ensure robust performance across multiple data sources
• Work with product development team on development and deployment
• Participate and lead research into the 3D scene
• Manage the acquisition of proprietary Red Green Blue - Depth dataset
• Design and implement networks for semantic segmentation, object detection, and depth estimation
• Help to recruit and lead a team of similarly qualified engineers
• Keeping track of the literature on compression techniques and Deep Learning optimizations

Skills: Application Requirements Definition, Annotation Process Management, Deep Learning Innovation, Performance Evaluation, Product Development Collaboration, 3D Scene Research, Dataset Acquisition, Network Design and Implementation

• Building and tuning neural networks
• Crafting and building models using text and/or audio
• Finding and building customer value in large data sets
• Participating in code reviews, brainstorming, and system architecture design.
• Rapidly prototyping models and experiments
• Staying up-to-date with, and in some cases advancing the state of the art in machine learning applications on conversational NLP data sets
• Promoting data science, machine learning, and AI approaches across development and technology teams
• Managing requirements and process for proper datasets gathering
• Tight collaboration with development and automation teams for model integration into production software
• Implementing the automatic retraining with reports in the cloud

Skills: Neural Network Tuning, Model Development, Customer Value Extraction, Code Review Participation, Rapid Prototyping, Conversational NLP Expertise, Promotion of AI Approaches, Dataset Management

• Researching state-of-the-art deep learning literature, implementing and experimenting with key concepts and deep learning models, then applying them to computer vision problems and OCR
• Liaising closely with the DevOps team to put the machine learning models into production
• Working with the data science team to design and develop client data processing pipelines, including data ingestion, cleaning, information extraction, fraud detection model calibration, etc.
• Working closely with senior management and stakeholders to understand needs and iterate on existing solutions
• Writing clean, production-ready code
• Inventing and applying state-of-the-art deep learning algorithms to solve problems related to building autonomous vehicles.
• Work on object detection, classification, and segmentation based on images, radar, and lidar data.
• Interaction with various internal product and research teams contributing toward building a self-driving car software solution as well as partners and customers
• Research and implementation of methods to increase the performance of the model

Skills: Deep Learning Research, Production Deployment, Data Processing Pipeline Design, Stakeholder Collaboration, Clean Code Writing, Algorithm Development, Object Detection and Segmentation, Performance Optimization

• Design and development of Neural Network Framework for object detection, video classification
• Perform Hyper-Parameter tuning and apply various Optimization techniques to enhance model performance.
• Design and develop Neural Network models for both unstructured and structured data.
• Perform image processing and develop tool/program for annotation and labeling of images
• Apply data mining techniques, statistical analysis and building high quality prediction systems.
• Verify seasonality, stationarity and trend of sequence data and develop forecasting models using LSTM, RNN etc.
• Design processes and tools to generate training sets
• Design, develop, and optimize Computer Vision, Machine Learning, and Deep Learning algorithms and models
• Be part of a dedicated development team that solves highly complex challenges

Skills: Neural Network Design, Hyper-Parameter Tuning, Model Development, Image Processing, Data Mining Techniques, Forecasting Model Development, Training Set Generation, Algorithm Optimization

• Experience in areas of Computer Vision, video processing, image processing, deep learning, and machine learning projects, including object detection, recognition, tracking and segmentation, understanding video content, CNN, etc.
• Capable of conducting applied research in machine learning, deep learning, and computer vision.
• Experience in deep learning frameworks (TensorFlow and/or PyTorch, etc.)
• Experience and proficiency in software programming using one or more of the following languages/tools, such as C/C++, Python, CUDA, OpenCV, etc.
• Strong in problem-solving
• Experience in cloud computing, such as Google Cloud and Amazon AWS
• Experience in NLP
• Experience training and deploying machine learning models at scale on distributed cloud environments
• Experience applying machine learning in the healthcare domain.
• Experience with reinforcement learning

Qualifications: BA in Mathematics with 4 years of Experience

• Have trained and deployed at least one deep learning model or ML algorithm for end users
• Experience with training models in multi-GPU settings
• Experience with CUDA
• Commercial experience with Machine Learning/Data Science
• Practical skills with Python
• Familiarity with TensorFlow, Keras or PyTorch
• Experience with technologies for efficient neural network training (various optimizers, regularization, transfer learning, etc)
• Knowledge of basic model quality assessment metrics
• Be autonomous, and a team player with a positive mindset.
• Creative and innovation focused.
• Have working proficiency in English.

Qualifications: BA in Electrical Engineering with 5 years of Experience

• Math background, deep knowledge of math statistics and probability theory
• Strong understanding of ML/DL algorithms and techniques
• Experience in production ML model implementation
• Corresponding level of Python coding skills, experience in related frameworks and libraries
• Experience in computer vision: detection/recognition, segmentation, classification
• OpenCV, Dlib experience
• Commercial experience developing deep learning solutions to computer vision problems
• Have experience in designing and training state-of-the-art Neural Networks applied to Computer Vision (e.g., object detection, tracking, segmentation).
• Have strong experience in Tensorflow or Pytorch.
• Be passionate about creating and adapting innovative techniques, or making them robust and scalable.

Qualifications: BA in Computer Science with 3 years of Experience

• Demonstrated experience with deep learning tasks for geometry, including depth and pose estimation, deep representations for 3D reconstruction, differentiable rendering, etc.
• Strong grasp of the traditional geometric foundations of 3D computer vision
• Self-motivated, a natural experimentalist, and a pro at debugging neural networks
• Mastery in one or more of the popular deep learning frameworks (e.g. Tensorflow, Pytorch)
• Strong software engineering or computer science background, with fluency in Python
• Deep learning and computer vision experience in industry
• Have experience building production computer vision models for deployment in the cloud
• Have experience working with Docker and Kubernetes
• Experience in developing, training and/or deploying state-of-the-art Deep Learning algorithms.
• Proficiency in Python as well as core ML libraries (e.g. PyTorch, Tensorflow, Keras)

Qualifications: BA in Data Science with 4 years of Experience

• Experience and demonstrated deep technical skills in one or more of the following areas: machine learning, recommendation systems, pattern recognition, natural language processing, or computer vision.
• Experience with DL frameworks such as Tensorflow or PyTorch.
• Experience with scientific and machine learning libraries e.g., SciPy, Scikit-learn, NumPy.
• Strong software development skills. 
• Proficiency in Python 
• Experience building large-scale data processing pipelines.
• Experience with Cloud computing, Hadoop/Spark, SQL.
• Ability to explain and present analyses and machine learning concepts to a broad audience.
• Ability to work with loosely defined objectives and turning these into concrete machine learning problems.
• Creative, collaborative, & product focused.

Qualifications: BA in Artificial Intelligence with 3 years of Experience

• Solid understanding of software engineering
• Expertise in machine learning and deep learning with a deep understanding of the underlying theory
• Expertise in reinforcement learning and unsupervised learning
• Experience in building and deploying impactful machine learning models in production
• Proficiency in Python
• Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch
• Experience in computer vision within a business or industrial context.
• Ability to write clean, efficient, well-documented code
• Familiarity with computer vision software libraries, including OpenCV
• Software debugging skills

Qualifications: BA in Computer Science with 2 years of Experience

• Proficient in Python, C/C++ and ARM or RISC-V assembly programming languages.
• Comfortable with matrix multiplication and related algorithms and tools (im2col, BLAS).
• Experience with bare-metal programming and embedded toolchains.
• Experience with LLVM, MLIR, TVM or GLOW
• Experience with CMSIS, TensorFlow Lite and TensorFlow Lite for Microcontrollers
• Industrial experience in deep learning and computer vision. 
• Comfortable with frameworks such as TensorFlow or PyTorch.
• Excellent spoken and written English.
• Experience in applied Deep Learning (DL) and Computer Vision (CV) concepts including but not limited to CNNs, RNNs, Autoencoders, Transfer Learning.
• Be passionate about creating and adapting innovative techniques, or making them robust and scalable.

Qualifications: BA in Data Science with 4 years of Experience

• In-depth knowledge of deep learning fundamentals.
• Strong mathematical aptitude, with emphasis on probability, vector algebra, and geometry.
• Proficiency in Python programming.
• Experience in conducting long-term development and/or research projects, in either academia or industry.
• Proficiency in English, both written and spoken.
• Hands-on experience with training deep learning models.
• Experience/knowledge in computer vision and image manipulation algorithms.
• Experience leading team projects and Linux.
• Proficiency in C++.
• Good programming skills with Python.

Qualifications: BA in Electrical Engineering with 3 years of Experience

• Proficiency with a deep learning framework such as TensorFlow or Keras
• Proficiency with Python and basic libraries for machine learning such as scikit-learn, numpy and pandas
• Proficiency with GAN and related technologies
• Great problem solving skills
• Expertise in visualizing and manipulating big datasets
• Proficiency with OpenCV
• Familiarity with Linux and AWS SageMaker experience 
• Ability to select hardware to run an ML model with the required latency
• Ability to adhere to company coding standards.
• Have working proficiency in English.

Qualifications: BA in Mathematics with 3 years of Experience

• Experience in machine learning (computer vision domain)
• Practical experience in at least one of the following problems: classification, detection, segmentation, metric learning
• Good understanding of machine learning and deep learning concepts
• Good written and spoken English
• Experience in deploying machine learning models to production
• Experience with C++
• Practical experience with GANs, VAEs
• Basic understanding of web and client-server architecture
• Knowledge of Algorithms, data structures, SQL, NoSQL, Docker, Kubernetes, Kubeflow
• Familiarity with AGILE development practices.
• Comfortable using collaborative development tools such as Git and Jira.

Qualifications: BA in Artificial Intelligence with 4 years of Experience