Computer Vision / Machine Learning

• 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.

• 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.

• 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.

Responsible to lead a team of analysts to build and deploy predictive models to infuse core business functions with deep analytical insights. The Senior Data Scientist will also work
closely with the Kinara management team to investigate strategically important business
questions.

Lead a team through the entire analytical and machine learning model life cycle:
 Define the problem statement
 Build and clean datasets
 Exploratory data analysis
 Feature engineering
 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

Skills:

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.

Hands-on experience in dealing with image data and CNN based architectures
• 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
analyses

APPLY LINK: http://bit.ly/2yipqSE Go through the entire job post thoroughly before pressing Apply. There is an eleven characters french word v*n*i*r*t*e mentioned somewhere in the whole text which is irrelevant to the context. You shall be required to enter this word while applying else application won't be considered submitted. ````````````````````````````````````````````````````````````````````````````````````````````````````` Aspirant - Data Science & AI Team: Sciences Full-Time, Trainee Bangaluru, India Relevant Exp: 0 - 10 Years Background: Top Tier institute Compensation: Above Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Busigence is a Decision Intelligence Company. We create decision intelligence products for real people by combining data, technology, business, and behavior enabling strengthened decisions. Scaling established startup by IIT alumni innovating & disrupting marketing domain through artificial intelligence. We bring those people onboard who are dedicated to deliver wisdom to humanity by solving the world’s most pressing problems differently thereby significantly impacting thousands of souls, everyday. We are a deep rooted organization with six years of success story having worked with folks from top tier background (IIT, NSIT, DCE, BITS, IIITs, NITs, IIMs, ISI etc.) maintaining an awesome culture with a common vision to build great data products. In past we have served fifty five customers and presently developing our second product, Robonate. First was emmoQ - an emotion intelligence platform. Third offering, H2HData, an innovation lab where we solve hard problems through data, science, & design. We work extensively & intensely on big data, data science, machine learning, deep learning, reinforcement learning, data analytics, natural language processing, cognitive computing, and business intelligence. First-and-Foremost Before you dive-in exploring this opportunity and press Apply, we wish you to evaluate yourself - We are looking for right candidate, not the best candidate. We love to work with someone who can mandatorily gel with our vision, beliefs, thoughts, methods, and values --- which are aligned with what can be expected in a true startup with ambitious goals. Skills are always secondary to us. Primarily, you must be someone who is not essentially looking for a job or career, rather starving for a challenge, you yourself probably don't know since when. A book can be written on what an applicant must have before joining a . For brevity, in nutshell, we need these three in you: 1. You must be [super sharp] (Just an analogue, but Irodov, Mensa, Feynman, Polya, ACM, NIPS, ICAAC, BattleCode, DOTA etc should have been your Done stuff. Can you relate solution 1 to problem 2? or Do you get confused even when solved similar problem in past? Are you able to grasp problem statement in one go? or get hanged?) 2. You must be [extremely energetic] (Do you raise eyebrows when asked to stretch your limits, both in terms of complexity or extra hours to put in? What comes first in your mind, let's finish it today or this can be done tomorrow too? Its Friday 10 PM at work -Tired?) 3. You must be [honourably honest] (Do you tell others what you think, or what they want to hear? Later is good for sales team for their customers, not for this role. Are you honest with your work? intrinsically with yourself first?) You know yourself the best. If not ask your loved ones and then decide. We clearly need exceedingly motivated people with entrepreneurial traits, not employee mindset - not at all. This is an immediate requirement. We shall have an accelerated interview process for fast closure - you would be required to be proactive and responsive. Real ROLE We are looking for students, graduates, and experienced folks with real passion for algorithms, computing, and analysis. You would be required to work with our sciences team on complex cases from data science, machine learning, and business analytics. Mandatory R1. Must know in-and-out of functional programming (https://docs.python.org/2/howto/functional.html) in Python with strong flair for data structures, linear algebra, & algorithms implementation. Only oops cannot not be accepted. R2. Must have soiled hands on methods, functions, and workarounds in NumPy, Pandas, Scikit-learn, SciPy, Stasmodels - collectively you should have implemented atleast 100 different techniques (we averaged out this figure with our past aspirants who have worked on this role) R3. Must have implemented complex mathematical logics through functional map-reduce framework in Python R4. Must have understanding on EDA cycle, machine learning algorithms, hyper-parameter optimization, ensemble learning, regularization, predictions, clustering, associations - at essential level R5. Must have solved atleast five problems through data science & machine learning. Mere coursera learning and/or Kaggle offline attempts shall not be accepted Preferred R6. Good to have required callibre to learn PySpark within four weeks once joined us R7. Good to have required callibre to grasp underlying business for a problem to be solved R8. Good to have understanding on CNNs, RNNs, MLP, Auto-Encoders - at basic level R9. Good to have solved atleast three problems through deep learning. Mere coursera learning and/or Kaggle offline attempts shall not be accepted R10. Good to have worked on pre-processing techniques for images, audio, and text - OpenCV, Librosa, NLTK R11. Good to have used pre-trained models - VGGNET, Inception, ResNet, WaveNet, Word2Vec Ideal YOU Y1. Degree in engineering, or any other data-heavy field at Bachelors level or above from a top tier institute Y2. Relevant experience of 0 - 10 years working on real-world problems in a reputed company or a proven startup Y3. You are a fanatical implementer who love to spend time with content, codes & workarounds, more than your loved ones Y4. You are true believer that human intelligence can be augmented through computer science & mathematics and your survival vinaigrette depends on getting the most from the data Y5. You are an entrepreneur mindset with ownership, intellectuality, & creativity as way to work. These are not fancy words, we mean it Actual WE W1. Real startup with Meaningful products W2. Revolutionary not just disruptive W3. Rules creators not followers W4. Small teams with real brains not herd of blockheads W5. Completely trust us and should be trusted back Why Us In addition to the regular stuff which every good startup offers – Lots of learning, Food, Parties, Open culture, Flexible working hours, and what not…. We offer you: You shall be working on our revolutionary products which are pioneer in their respective categories. This is a fact. We try real hard to hire fun loving crazy folks who are driven by more than a paycheck. You shall be working with creamiest talent on extremely challenging problems at most happening workplace. How to Apply You should apply online by clicking "Apply Now". For queries regarding an open position, please write to [email protected] For more information, visit http://www.busigence.com Careers: http://careers.busigence.com Research: http://research.busigence.com Jobs: http://careers.busigence.com/jobs/data-science Feel right fit for the position, mandatorily attach PDF resume highlighting your A. Key Skills B. Knowledge Inputs C. Major Accomplishments D. Problems Solved E. Submissions – Github/ StackOverflow/ Kaggle/ Euler Project etc. (if applicable) If you don't see this open position that interests you, join our Talent Pool and let us know how you can make a difference here. Referrals are more than welcome. Keep us in loop.

-Precily AI: Automatic summarization, shortening a business document, book with our AI. Create a summary of the major points of the original document. AI can make a coherent summary taking into account variables such as length, writing style, and syntax. We're also working in the legal domain to reduce the high number of pending cases in India. We use Artificial Intelligence and Machine Learning capabilities such as NLP, Neural Networks in Processing the data to provide solutions for various industries such as Enterprise, Healthcare, Legal.

Does the current state of media frustrate you? Do you want to change the way we consume news? Are you a kickass machine learning practitioner and aspiring entrepreneur, who has opinions on world affairs as well? If so, continue reading! We at UnFound are developing a product which simplifies complex and cluttered news into simple themes, removes bias by showing all (& often unheard of) perspectives, and produce crisp summaries- all with minimal human intervention! We are looking for passionate and experienced machine learning ENGINEER/INTERN, *preferably* with experience in NLP. We want someone who can take initiatives. If you need to be micro-managed, this is NOT the role for you. 1. Demonstrable background in machine learning, especially NLP, information retrieval, etc. 2. Hands on with popular data science frameworks- Python, Jupyter, TensorFlow, PyTorch. 3. Implementation ready background in deep learning techniques like word embeddings, CNN, RNN/LSTM, etc. 4. Experience with productionizing machine learning solutions, especially ML powered mobile/ web-apps/ BOTs. 5. Hands on experience on AWS, and other cloud platforms. GPU experience is strongly preferred. 6. Thorough understanding of back-end concepts, and databases (SQL, Postgres, NoSQL, etc.) 7. Good Kaggle (or similar) scores, MOOC (Udacity, Coursera, fast.ai, etc.) preferred.