Deep Learning
Data Science
Scala
Machine Learning (ML)Basic Qualifications:
∙Bachelors in Computer Science/Mathematics + Research (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from Tier1 tech institutes.
∙3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems.
∙1 year or more of experience specifically with deep learning (CNN, RNN, LSTM, RBM etc).
∙Strong working knowledge of deep learning, machine learning, and statistics.
- Deep domain understanding of Personalization, Search and Visual.
∙Strong math skills with statistical modeling / machine learning.
∙Hands-on experience building models with deep learning frameworks like MXNet or Tensorflow.
∙Experience in using Python, statistical/machine learning libs.
∙Ability to think creatively and solve problems.
∙Data presentation skills.
Preferred:
∙MS/ Ph.D. (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from IISc and other Top Global Universities.
∙Or, Publications in highly accredited journals (If available, please share links to your published work.).
∙Or, history of scaling ML/Deep learning algorithm at massively large scale.
Subodh Popalwar
Software Engineer, Memorres
About Couture.ai
Couture.ai is founded by global innovators and entrepreneurs with experience and self-funding of creating global startup success stories in past. The core team consists of some of the best minds in India in Machine learning and Deep learning research.
Similar jobs
Data ScienceMachine Learning (ML)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 AI and audio technologies around audio detection, speech-to-text, interpretation, and sentiment analysis.
You will be responsible for:
Developing audio algorithms to detect key moments within popular online games, such as:
Streamer speaking, shouting, etc.
Gunfire, explosions, and other in-game audio events
Speech-to-text and sentiment analysis of the streamer’s narration
Leveraging baseline technologies such as TensorFlow and others -- and building models on top of them
Building neural network architectures for audio 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 AI frameworks and algorithms, especially pertaining to audio analysis, speech-to-text, sentiment analysis, and natural language processing
Experience using Python, TensorFlow and other AI tools
Demonstrated understanding of various algorithms for audio analysis, such as CNNs, LSTM for natural language processing, and others
Nice to have: some familiarity with AI-based audio analysis including sentiment analysis
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, Audio Analysis, Sentiment Analysis, Speech-To-Text, Natural Language Processing, Neural Networks, TensorFlow, OpenCV, AWS, Python
Work Experience: 2 years to 10 years
About Sizzle
Sizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Presently, there are over 700 million fans around the world that watch gaming videos on Twitch and YouTube. Sizzle is creating a new highlights experience for these fans, so they can catch up on their favorite streamers and esports leagues. Sizzle is available at http://www.sizzle.gg">www.sizzle.gg.
ScalaWHAT YOU WILL DO:
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● Create and maintain optimal data pipeline architecture.
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● Assemble large, complex data sets that meet functional / non-functional business requirements.
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● Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, re-designing infrastructure for greater scalability, etc.
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● Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide
variety of data sources using Spark,Hadoop and AWS 'big data' technologies.(EC2, EMR, S3, Athena).
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● Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition,
operational efficiency and other key business performance metrics.
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● Work with stakeholders including the Executive, Product, Data and Design teams to assist with
data-related technical issues and support their data infrastructure needs.
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● Keep our data separated and secure across national boundaries through multiple data centers and AWS
regions.
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● Create data tools for analytics and data scientist team members that assist them in building and
optimizing our product into an innovative industry leader.
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● Work with data and analytics experts to strive for greater functionality in our data systems.
REQUIRED SKILLS & QUALIFICATIONS:
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● 5+ years of experience in a Data Engineer role.
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● Advanced working SQL knowledge and experience working with relational databases, query authoring
(SQL) as well as working familiarity with a variety of databases.
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● Experience building and optimizing 'big data' data pipelines, architectures and data sets.
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● Experience performing root cause analysis on internal and external data and processes to answer
specific business questions and identify opportunities for improvement.
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● Strong analytic skills related to working with unstructured datasets.
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● Build processes supporting data transformation, data structures, metadata, dependency and workload
management.
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● A successful history of manipulating, processing and extracting value from large disconnected datasets.
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● Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
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● Strong project management and organizational skills.
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● Experience supporting and working with cross-functional teams in a dynamic environment
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● Experience with big data tools: Hadoop, Spark, Pig, Vetica, etc.
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● Experience with AWS cloud services: EC2, EMR, S3, Athena
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● Experience with Linux
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● Experience with object-oriented/object function scripting languages: Python, Java, Shell, Scala, etc.
PREFERRED SKILLS & QUALIFICATIONS:
● Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
Job responsibilities
- You will partner with teammates to create complex data processing pipelines in order to solve our clients' most complex challenges
- You will collaborate with Data Scientists in order to design scalable implementations of their models
- You will pair to write clean and iterative code based on TDD
- Leverage various continuous delivery practices to deploy, support and operate data pipelines
- Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available
- Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions
- Create data models and speak to the tradeoffs of different modeling approaches
- Seamlessly incorporate data quality into your day-to-day work as well as into the delivery process
- Assure effective collaboration between Thoughtworks' and the client's teams, encouraging open communication and advocating for shared outcomes
- You have a good understanding of data modelling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop
- You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting
- Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions
- You are comfortable taking data-driven approaches and applying data security strategy to solve business problems
- Working with data excites you: you can build and operate data pipelines, and maintain data storage, all within distributed systems
- You're genuinely excited about data infrastructure and operations with a familiarity working in cloud environments
- Professional skills
- You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives
- An interest in coaching, sharing your experience and knowledge with teammates
- You enjoy influencing others and always advocate for technical excellence while being open to change when needed
- Presence in the external tech community: you willingly share your expertise with others via speaking engagements, contributions to open source, blogs and more
Data ScienceMachine Learning (ML)
R Programming
PythonDeep LearningJob Responsibilities:-
- Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
- Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
- Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
- Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
- Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
- Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
- Experience working with big data systems and big data concepts.
- Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
- Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
- Experience with noisy and/or unstructured textual data.
knowledge graph and NLP including summarization, topic modelling etc
- Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
- Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
- Strong understanding of text pre-processing and normalization techniques, such as tokenization,
- POS tagging and parsing and how they work at a low level.
- Excellent problem solving skills.
- Strong verbal and written communication skills
- Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
- Practical experience in using NLP related techniques and algorithms
- Experience in open source coding and communities desirable.
Able to containerize Models and associated modules and work in a Microservices environment
Data ScienceMust have experience on e-commerce projects
Machine Learning (ML)ML Engineer-Analyst/ Senior Analyst
Job purpose:
To design and develop machine learning and deep learning systems. Run machine learning tests andexperiments and implementing appropriate ML algorithms. Works cross-functionally with the Data Scientists, Software application developers and business groups for the development of innovative ML models. Use Agile experience to work collaboratively with other Managers/Owners in geographically distributed teams.
Accountabilities:
- Work with Data Scientists and Business Analysts to frame problems in a business context. Assist all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
- Understand business objectives and developing models that help to achieve them, along with metrics to track their progress.
- Explore and visualize data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world.
- Define validation strategies, preprocess or feature engineering to be done on a given dataset and data augmentation pipelines.
- Analyze the errors of the model and design strategies to overcome them.
- Collaborate with data engineers to build data and model pipelines, manage the infrastructure and data pipelines needed to bring code to production and demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
Qualifications & Specifications
- Bachelor's degree in Engineering /Computer Science/ Math/ Statistics or equivalent. Master's degree in relevant specification will be first preference
- Experience of machine learning algorithms and libraries
- Understanding of data structures, data modeling and software architecture.
- Deep knowledge of math, probability, statistics and algorithms
- Experience with machine learning platforms such as Microsoft Azure, Google Cloud, IBM Watson, and Amazon
- Big data environment: Hadoop, Spark
- Programming languages: Python, R, PySpark
- Supervised & Unsupervised machine learning: linear regression, logistic regression, k-means
clustering, ensemble models, random forest, svm, gradient boosting
- Sampling data: bagging & boosting, bootstrapping
- Neural networks: ANN, CNN, RNN related topics
- Deep learning: Keras, Tensorflow
- Experience with AWS Sagemaker deployment and agile methodology
Data ScienceMachine Learning (ML)Python- Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
- Implement data pipelines, new features, and algorithms that are critical to our production models
- Create scalable strategies to deploy and execute your models
- Write well designed, testable, efficient code
- Identify valuable data sources and automate collection processes.
- Undertake to preprocess of structured and unstructured data.
- Analyze large amounts of information to discover trends and patterns.
Requirements:
- 2+ years of experience in applied data science or engineering with a focus on machine learning
- Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
- strong quantitative and programming skills with a product-driven sensibility
Data ScienceDeep LearningR ProgrammingPythonMachine Learning (ML)1. Expert in deep learning and machine learning techniques,
2. Extremely Good in image/video processing,
3. Have a Good understanding of Linear algebra, Optimization techniques, Statistics and pattern recognition.
Then u r the right fit for this position.
Machine Learning (ML)MTX Group Inc. is seeking a motivated Technical Lead - AI to join our team. MTX Group Inc. is a global implementation partner enabling organizations to become fit enterprises. MTX provides expertise across various platforms and technologies, including Google Cloud, Salesforce, artificial intelligence/machine learning, data integration, data governance, data quality, analytics, visualization and mobile technology. MTX’s very own Artificial Intelligence platform Maverick, enables clients to accelerate processes and critical decisions by leveraging a Cognitive Decision Engine, a collection of purpose-built Artificial Neural Networks designed to leverage the power of Machine Learning. The Maverick Platform includes Smart Asset Detection and Monitoring, Chatbot Services, Document Verification, to name a few.
Responsibilities:
- Extensive research and development of new AI/ML techniques that enables learning
the semantics of data (images, video, text, audio, speech, etc)
- Improving the existing ML and DNN models and products through R&D on cutting edge technologies
- Collaborate with Machine Learning teams to drive innovation of complex and accurate cognitive system
- Collaborate with Engineering and Core team to drive innovation of scalable ML and AI serving production platforms
- Create POCs to quickly test a new model architecture and create improvement over an existing methodology
- Introduce major innovations that can result in better product features and develop strategies and plans required to drive these
- Lead a team and collaborate with product managers, tech review complex implementations and provide optimisation best practices
What you will bring:
- 4-6 years of Experience
- Experience in neural networks, graphical models, reinforcement learning, and natural language processing
- Experience in Computer Vision techniques and image detection neural network models like semantic segmentation, instance segmentation, object detection, etc
- In-depth understanding of benchmarking, parallel computing, distributed computing, machine learning, and AI
- Programming experience in one or more of the following: Python, C, C++, C#, Java, R, and toolkits such as Tensorflow, Keras, PyTorch, Caffe, MxNet, SciPy, SciKit, etc
- Ability to perform research that is justified and guided by business opportunities
- Demonstrated successful implementation if industry grade AI solutions in the past
- Ability to lead a team of AI engineers in an agile development environment
What we offer:
- Group Medical Insurance (Family Floater Plan - Self + Spouse + 2 Dependent Children)
- Sum Insured: INR 5,00,000/-
- Maternity cover upto two children
- Inclusive of COVID-19 Coverage
- Cashless & Reimbursement facility
- Access to free online doctor consultation
- Personal Accident Policy (Disability Insurance) -
- Sum Insured: INR. 25,00,000/- Per Employee
- Accidental Death and Permanent Total Disability is covered up to 100% of Sum Insured
- Permanent Partial Disability is covered as per the scale of benefits decided by the Insurer
- Temporary Total Disability is covered
- An option of Paytm Food Wallet (up to Rs. 2500) as a tax saver benefit
- Monthly Internet Reimbursement of upto Rs. 1,000
- Opportunity to pursue Executive Programs/ courses at top universities globally
- Professional Development opportunities through various MTX sponsored certifications on multiple technology stacks including Salesforce, Google Cloud, Amazon & others
Data ScienceR Programming
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Software Engineer, Memorres