Please apply if and only if you enjoy engineering, wish to write a lot of code, wish to do a lot of hands-on Python experimentation, already have in-depth knowledge of deep learning. This position is strictly for people having knowledge various Neural networks and can customize the neural network and not for people who have experience in downloading various AI/ML code. This position is not for freshers. We are looking for candidates with AI/ML/CV experience of at least 2 year in the industry.
How often have you read job descriptions and gone ‘I have read this before’ or ‘the real job description will come out during the interviews, so why bother reading this’. In other instances when job descriptions are actually well-written, ie not just copied and pasted from somewhere and try doing justice to what you’d be doing at the job, 2-4 months of a typical interview cycle make those descriptions obsolete by the time you actually start at the job. Also not unsurprising then: just like you ignore or skim through job descriptions, most recruiters do the same with your resumes – look for specific keywords and leave all the assessment for during the interview itself. Even worse: the human recruiter in some cases is being replaced by an algorithm to automate screening. You, therefore, will try to put as many keywords in your resume to ensure you get that interview call. Nobody is being ingenuine in this process but the very process is fundamentally broken. And that is exactly what we want to solve: create an effective ‘matching of work to the worker’ that is an accurate and real-time reflection of both ends, thus increasing the actual engagement with the work itself. Responsibilities In this role, you’ll build and implement novel Machine Learning and Deep Learning systems on our platform as well as help build the infrastructure to train and deploy them. Specifically, you will: - Design and implement the infrastructure required to train models at scale. - Work with the data team’s infrastructure to build real-time and offline feature databases. - Work with the data team to create the infrastructure to build and maintain the datasets from which models are created - Build the model serving systems with which we can deploy our models to production - As we grow, scale the ML system to be able to support more use cases and ML model types. Requirements - 1+ years of experience building production-ready ML models and systems. - 3+ years of building distributed systems and/or scalable backend systems and the ability to maintain such systems in production. - Strong software engineering fundamentals - understanding of data structures and algorithms, O-notation, ability to maintain a test suite and write clear maintainable code. - Familiarity with the majority of the following tools: Tensorflow, Numpy, Scipy, SparkML, pandas, scikit-learn. - Demonstrated leadership and self-direction and willingness to both teach others and learn new techniques. - Experience with big data processing and storage systems: Hadoop, Spark, Hbase, Cassandra etc. - Strong programming skills in Python. Intermediate to Advanced knowledge of SQL and ability to wrangle data from many disparate data sources - Technologies we use: MySQL, Python, AWS, Snowflake, R, and Looker, among many others.
Core Job Responsibilities: - Build, Tune and Optimize Machine Learning models on Google Cloud Platform - Work with large/complex datasets to solve challeging and non-routine analysis problems, applying advanced analytical methods and techniques. - Build and prototype data pipelines for analysis at scale. - Work cross-functionally with Business Analysts and Data Engineers to help develop cutting edge and innovative artificial intelligence and machine learning models. - Make recommendations for selections on machine learning models. - Drive accuracy levels to the next stage of the given ML models. Minimum qualifications: - 2 to 5 years of relevant work experience in Machine Learning and Advanced Analytics (e.g., as a Machine Learning Specialist / Data scientist ). - Strong experience using artificial intelligence frameworks such as Tensorflow, sci-kit learn, Keras using python. - Good in Python/Nodejs programming. - Good understanding of Cloud platforms like GCP, AWS, or Azure. Must Have skills : -Work experience in building data pipelines to ingest, cleanse and transform data. - Experience of working in Manufacturing, Retail, Hi-Tech or Healthcare industry. - Applied experience with machine learning on large datasets. - Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. - Demonstrated skills in selecting the right statistical tools given a data analysis problem. - Demonstrated effective written and verbal communication skills. - Demonstrated willingness to both teach others and learn new techniques.
Profile Brief/ Responsibilities • Keep up-to-date with latest technology trends. • Work closely with Project/Business/Research teams for identifying the best model for a given problem • Research and build highly efficient and state-of-the art models • Selecting features, building and optimizing models using machine learning techniques. Requirements • 2-5 years of relevant industrial experience in Machine Learning and Deep Learning with: Strong working knowledge in Python, C, C++, Linux. • Excellent understanding of Machine Learning Techniques and Algorithms. • Excellent understanding of Text Analytics concepts and methodologies - Named Entity Recognition, Text Classification, Event Detection, Sentiment Analysis, POS Tagging, Bag of Words. • Hands-on experience with Neural Networks (CNN/, RNN,/ DNN, /BNN,/LSTM, SSD, etc), Support Vector Machine, Conditional Random Field etc. • Experience with GPU/DSP/ISP/SoC architecture and system software • Python, Tensorflow/Caffe/CUDA/Keras • Ability to see big picture, think innovative and suggest out of box solutions. • Ability to write high performance structured code. • Exposure to recent developments in Deep Learning domain
The Computer Vision engineer will be required to build algorithms based on our existing product portfolio and develop cutting-edge solutions for the emerging requirements of our key markets. The candidate will have the opportunity to interact and collaborate with our team of global Computer Vision experts in developing cutting-edge solutions to meet the dynamic nature of requirements for our customers. Key Responsibilities: a. Designing and implementing efficient computer vision algorithms for recognizing, tracking Human subjects within a controlled environment b. Architecting algorithms to work onboard our hardware systems as well as in the cloud where appropriate. c. Work together with our software development team to develop a scalable software solution Required Experience a. Minimum of 2-4 years of Relevant experience. b. MS, or PhD in Computer Science, Applied Mathematics, or a related field. c. Strong knowledge of the state-of-the-art in computer vision and machine learning algorithms with a solid understanding of OpenCV d. Experience working with point cloud processing and Point Cloud Library (PCL) e. Experience in optimization for computer vision (E.g. Semantic segmentation, depth reconstruction, scene flow) f. Ability to write efficient and maintainable code g. Solid understanding of C++ and/or Python, preferably in a Linux environment h. Possess practical experience in TensorFlow, Caffe. Desired Experience a. Prior experience in working with depth sensors and 3D Reconstruction using computer vision, image processing techniques b. Familiarity with the State-of-the-art in Computer vision and Deep Learning techniques