Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
- 3+ years of Experience majoring in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions.
- Programming skills in Python, knowledge in Statistics.
- Hands-on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, parameter tuning, etc.). Familiarity with reinforcement learning is highly desirable.
- Experience in the financial domain and familiarity with financial models are highly desirable.
- Experience in image processing and computer vision.
- Experience working with building data pipelines.
- Good understanding of Data preparation, Model planning, Model training, Model validation, Model deployment and performance tuning.
- Should have hands on experience with some of these methods: Regression, Decision Trees,CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Support Vector Machines, Ensemble Methods, Association Rules, Principal Component Analysis, Clustering, ArtificiAl Intelligence
- Should have experience in using larger data sets using Postgres Database.
We are seeking a dedicated Machine Learning Engineer to join our growing company.
You will collaborate with software engineers and product managers to create efficient artificial intelligence algorithms. As an ML Engineer, we hope you can put your passion for AI engineering towards solving amazing problems through AI.
Roles and Responsibility
- Develop Machine Learning (ML) models using various neural network architectures and implement the model using Python.
- Understand the problem by interacting with domain experts and design/implement various training algorithms and feature detectors.
- Train models using various datasets and optimize the inference architecture for performance.
- Continuously work to improve the Recall accuracy and precision metrics for ML models.
- Design and implement event driven pipelines using Kafka, Python, Keras, Pytorch and Tensorflow.
- Perform data clean-up and guide the labelling team to create labelled datasets.
- Work with different engineers to implement inference graphs, infographics and automated report/alert generation.
- Debug, build, test and release complete software products under SaaS model.
Bonus points for -
- Experience developing and consuming REST APIs.
- Knowledge of developing dockerized micorservices-based architecture to ensure scalability.
Job Qualifications and Skill Sets
- 1-2 years of relevant experience.
- Proven experience as a software developer with knowledge about software development lifecycle (SDLC), from design to implementation.
- Knowledge of scripting languages (e.g. Python)
- Experience with deep learning frameworks (e.g., PyTorch, Tensorflow etc) and software stack (e.g., TensorRT, TVM, etc)
- Experience with model optimization techniques like pruning, quantization, NAS, etc.
- Experience with ML accelerators and hardware architecture, e.g., GPUs, TPUs, NNAs, MLAs Experience with modern parallel programming: GPU programming (CUDA, OpenCL), SIMD (avx, neon/SVE), multi-process and multi-threaded designs.
- Familiarity with HW vendors' deep learning stacks (e.g., cuDNN, cuBLAS, AMD MIOpen, TensorRT, OpenVino, ARM Compute Library, etc)
- Experience with version control systems such as Git and offerings such as GitHub, BitBucket etc.
Bonus points for -
- Familiarity with databases (e.g. MySQL, MongoDB, Cassandra), web servers (e.g. Apache, NGINX), UI/UX design.
- Exposure to edge/mobile-based ML is a plus.
closely with the Kinara management team to investigate strategically important business
Lead a team through the entire analytical and machine learning model life cycle:
Define the problem statement
Build and clean datasets
Exploratory data analysis
Apply ML algorithms and assess the performance
Code for deployment
Code testing and troubleshooting
Communicate Analysis to Stakeholders
Manage Data Analysts and Data Scientists
Job roles and responsibilities:
- Design, develop, test, deploy, maintain and improve ML models/infrastructure and software that uses these models
- Experience writing software in one or more languages such as Python, Scala, R, or similar with strong competencies in data structures, algorithms, and software design
- Experience working with recommendation engines, data pipelines, or distributed machine learning
- Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano)
- Knowledge of data analytics concepts, including bigdata, data warehouse technical architectures, ETL and reporting/analytic tools and environments
- Participate in cutting edge research in artificial intelligence and machine learning applications
- Contribute to engineering efforts from planning and organization to execution and delivery to solve complex, real world engineering problems
- Working knowledge on different Algorithms and Machine Learning techniques like, Linear & Logistic Regression analysis, Segmentation, Decisions trees, Cluster analysis and factor analysis, Time Series Analysis, K-Nearest Neighbour, K-Means algorithm, Random Forests Algorithm, NLP (Natural language processing), Sentimental analysis, various Artificial Neural Networks, Convolution Neural Nets (CNN), Bidirectional Recurrent Neural Networks (BRNN)
- Demonstrated excellent communication, presentation, and problem-solving skills
Technical Skills Required:
- GCP Native AI/ML services like Vision, NLP, Document AI, Dialogflow, CCAI, BQ etc.,
- Proficiency with a deep learning framework such as TensorFlow or Keras, etc.,
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas, jupyter notebook
- Expertise in visualizing and manipulating big datasets
- Ability to select hardware to run an ML model with the required latency
- Good to have MLOps and Kubeflow knowledge
- GCP ML Engineer Certification
Sizzle is an exciting new startup that’s changing the world of gaming. At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. We’re looking for a superstar engineer that is well versed with computer vision and AI technologies around image and video analysis.
You will be responsible for:
- Developing computer vision algorithms to detect key moments within popular online games
- Leveraging baseline technologies such as TensorFlow, OpenCV, and others -- and building models on top of them
- Building neural network (CNN) architectures for image and video analysis, as it pertains to popular games
- Specifying exact requirements for training data sets, and working with analysts to create the data sets
- Training final models, including techniques such as transfer learning, data augmentation, etc. to optimize models for use in a production environment
- Working with back-end engineers to get all of the detection algorithms into production, to automate the highlight creation
You should have the following qualities:
- Solid understanding of computer vision and AI frameworks and algorithms, especially pertaining to image and video analysis
- Experience using Python, TensorFlow, OpenCV and other computer vision tools
- Understand common computer vision object detection models in use today e.g. Inception, R-CNN, Yolo, MobileNet SSD, etc.
- Demonstrated understanding of various algorithms for image and video analysis, such as CNNs, LSTM for motion and inter-frame analysis, and others
- Familiarity with AWS environments
- Excited about working in a fast-changing startup environment
- Willingness to learn rapidly on the job, try different things, and deliver results
- Ideally a gamer or someone interested in watching gaming content online
Machine Learning, Computer Vision, Image Processing, Neural Networks, TensorFlow, OpenCV, AWS, Python
Seniority: We are open to junior or senior engineers. We're more interested in the proper skillsets.
Salary: Will be commensurate with experience.
Who Should Apply:
If you have the right experience, regardless of your seniority, please apply. However, if you don't have AI or computer vision experience, please do not apply.
• Should have worked on deep learning frameworks (like tensorflow, keras, pytorch, etc)
• Proficient in Python and using packages like Numpy, Pandas
• Good understanding of data structures and algorithms along with Statistics, Linear Algebra and Calculus
• Mathematical intuition of ML and DL algorithms
• Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
We are looking for an engineer with ML/DL background.
Ideal candidate should have the following skillset
3) Experience building and deploying systems
4) Experience with Theano/Torch/Caffe/Keras all useful
5) Experience Data warehousing/storage/management would be a plus
6) Experience writing production software would be a plus
7) Ideal candidate should have developed their own DL architechtures apart from using open source architechtures.
8) Ideal candidate would have extensive experience with computer vision applications
Candidates would be responsible for building Deep Learning models to solve specific problems. Workflow would look as follows:
1) Define Problem Statement (input -> output)
2) Preprocess Data
3) Build DL model
4) Test on different datasets using Transfer Learning
5) Parameter Tuning
6) Deployment to production
Candidate should have experience working on Deep Learning with an engineering degree from a top tier institute (preferably IIT/BITS or equivalent)