11+ Natural Language Toolkit (NLTK) Jobs in Bangalore (Bengaluru) | Natural Language Toolkit (NLTK) Job openings in Bangalore (Bengaluru)

About the role: We are looking for a Natural Language Processing (NLP)/ML Engineer to help us improve our NLP products and create new NLP applications. This is a highly technical role and an excellent academic and/or industry background (with specialization in NLP) with a Master's is preferred.

Someone who has strong industrial experience in NLP for a period of 2+ years. Experienced in applying different NLP techniques to problems such as text classification, text summarization, question &answering, information retrieval, knowledge extraction, and conversational bots design potentially with both traditional & Deep Learning Techniques. In-depth exposure to some of the Tools/Techniques: SpaCy, NLTK, Gensim, CoreNLP, NLU, NLG tools etc. Ability to design & develop practical analytical approach keeping the context of data quality & availability, feasibility, scalability, turnaround time aspects. Desirable to have demonstrated capability to integrate NLP technologies to improve chatbot experience. Exposure to frameworks like DialogFlow, RASA NLU, LUIS is preferred. Contributions to open-source software projects are an added advantage.

Experience in analyzing large amounts of user-generated content and process data in large-scale environments using cloud infrastructure is desirable

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. 

Greetings!!

We are looking for a Machine Learning engineer for on of our premium client.
Experience: 2-9 years
Location: Gurgaon/Bangalore
Tech Stack:
Python, PySpark, the Python Scientific Stack; MLFlow, Grafana, Prometheus for machine learning pipeline management and monitoring; SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS; Django, GraphQL and ReactJS for horizontal product development; container technologies such as Docker and Kubernetes, CircleCI/Jenkins for CI/CD, cloud solutions such as AWS, GCP, and Azure as well as Terraform and Cloudformation for deployment

Company Profile
XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with large data sets to find
opportunities for product and process optimization and using models to test the effectiveness of different courses of
action. They must have knowledge using a variety of data mining/data analysis methods, using a variety of data tools,
building, and implementing models, using/creating algorithms, and creating/running simulations. They must be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.

● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.

Roles and Responsibilities:
As an Associate Manager - Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve
predefined outcomes.

• Engage with clients to understand current and future business goals and translate business
problems into analytical frameworks
• Develop custom models based on an in-depth understanding of underlying data, data structures,
and business problems to ensure deliverables meet client needs
• Create repeatable, interpretable and scalable models
• Effectively communicate the analytics approach and insights to a larger business audience
• Collaborate with team members, peers and leadership at Tredence and client companies

Qualification:
1. Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics,
statistics) or equivalent experience.
2. 5+ years of experience in data science, building hands-on ML models
3. Experience leading the end-to-end design, development, and deployment of predictive
modeling solutions.
4. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data
analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc.
5. Advanced SQL skills with SQL Server and Spark experience.
6. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms
(Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks
7. Experience with Natural Language Processing (NLTK) and text analytics for information
extraction, parsing and topic modeling.
8. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills.
Thrive in a fast-paced, innovative environment
9. Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred
10. Experience with cloud platforms such as Azure, AWS is preferred but not required

Skill Set:

• 4+ years of experience Solid understanding of Python, Java and general software development skills (source code management, debugging, testing, deployment etc.).
• Experience in working with Solr and ElasticSearch Experience with NLP technologies & the handling of unstructured text Detailed understanding of text pre-processing and normalisation techniques such as tokenisation, lemmatisation, stemming, POS tagging etc.
• Prior experience in implementation of traditional ML solutions - classification, regression or clustering problem Expertise in text-analytics - Sentiment Analysis, Entity Extraction, Language modelling - and associated sequence learning models ( RNN, LSTM, GRU).
• Comfortable working with deep-learning libraries (eg. PyTorch)
• Candidate can even be a fresher with 1 or 2 years of experience IIIT, IIIT, Bits Pilani, top 5 local colleges are preferred colleges and universities.
• A Masters candidate in machine learning.
• Can source candidates from Mu Sigma and Manthan.

Hiring for Machine Learning Deep Learning, who have build solutions for computer vision ,nlp, Tensorflow, Pytorch, Tensorflow Lite for Android phone 

JD : ML/NLP Tech Lead

- We are looking to hire an ML/NLP Tech lead who can own products for a technology perspective and manage a team of up to 10 members. You will play a pivotal role in re-engineering our products, transformation, and scaling of AssessEd

WHAT ARE WE BUILDING :

- A revolutionary way of providing continuous assessments of a child's skill and learning, pointing the way to the child's potential in the future. This as opposed to the traditional one-time, dipstick methodology of a test that hurriedly bundles the child into a slot, that in-turn - declares- the child to be fit for a career in a specific area or a particular set of courses that would perhaps get him somewhere. At the core of our system is a lot of data - both structured and unstructured. 

 

- We have books and questions and web resources and student reports that drive all our machine learning algorithms. Our goal is to not only figure out how a child is coping but to also figure out how to help him by presenting relevant information and questions to him in topics that he is struggling to learn.

Required Skill sets :

- Wisdom to know when to hustle and when to be calm and dig deep. Strong can do mentality, who is joining us to build on a vision, not to do a job.

- A deep hunger to learn, understand, and apply your knowledge to create technology.

- Ability and Experience tackling hard Natural Language Processing problems, to separate wheat from the chaff, knowledge of mathematical tools to succinctly describe the ideas to implement them in code.

- Very Good understanding of Natural Language Processing and Machine Learning with projects to back the same.

- Strong fundamentals in Linear Algebra, Probability and Random Variables, and Algorithms.

- Strong Systems experience in Distributed Systems Pipeline: Hadoop, Spark, etc.

- Good knowledge of at least one prototyping/scripting language: Python, MATLAB/Octave or R.

- Good understanding of Algorithms and Data Structures.

- Strong programming experience in C++/Java/Lisp/Haskell.

- Good written and verbal communication.

Desired Skill sets :

- Passion for well-engineered product and you are - ticked off- when something engineered is off and you want to get your hands dirty and fix it.

- 3+ yrs of research experience in Machine Learning, Deep Learning and NLP

- Top tier peer-reviewed research publication in areas like Algorithms, Computer Vision/Image Processing, Machine Learning or Optimization (CVPR, ICCV, ICML, NIPS, EMNLP, ACL, SODA, FOCS etc)

- Open Source Contribution (include the link to your projects, GitHub etc.)

- Knowledge of functional programming.

- International level participation in ACM ICPC, IOI, TopCoder, etc

 

- International level participation in Physics or Math Olympiad

- Intellectual curiosity about advanced math topics like Theoretical Computer Science, Abstract Algebra, Topology, Differential Geometry, Category Theory, etc.

What can you expect :

- Opportunity to work on the interesting and hard research problem, to see the real application of state-of-the-art research into practice.

- Opportunity to work on important problems with big social impact: Massive, and direct impact of the work you do on the lives of students.

- An intellectually invigorating, phenomenal work environment, with massive ownership and growth opportunities.

- Learn effective engineering habits required to build/deploy large production-ready ML applications.

- Ability to do quick iterations and deployments.

- We would be excited to see you publish papers (though certain restrictions do apply).

Website : http://Digitalaristotle.ai


Work Location: - Bangalore

BS/Masters in Computer Science with 4+ years of experience. Excellent knowledge in algorithms and data structures and implementing them in Java. Experience in distributed systems architectures, including multithreading & concurrency issues. Experience working in Agile/Scrum environment is desired. Exceptional debugging, testing, and problem-solving skills. Self-starter, with quick learning curve. Strong written and verbal communication skills and an ability and interest to mentor other junior engineers. Working experience within product development teams is a must. Must have demonstrated capabilities to create patentable ideas. Working experience in Natural Language Processing (NLP)/Natural Language Understanding (NLU) based solutions is a plus.

We at artivatic are seeking passionate, talented and research focused natural processing language engineer with strong machine learning and mathematics background to help build industry-leading technology. - The ideal candidate will have research/implementation experience modeling and developing NLP tools and experience working with machine learning/deep learning algorithms.Qualifications :- Bachelors or Master degree in Computer Science, Mathematics or related field with specialization in natural language processing, Machine Learning or Deep Learning.- Publication record in conferences/journals is a plus.- 2+ years of working/research experience building NLP based solutions is preferred.Required Skills :- Hands-on Experience building NLP models using different NLP libraries ad toolkit like NLTK, Stanford NLP etc.- Good understanding of Rule-based, Statistical and probabilistic NLP techniques.- Good knowledge of NLP approaches and concepts like topic modeling, text summarization, semantic modeling, Named Entity recognition etc.- Good understanding of Machine learning and Deep learning algorithms.- Good knowledge of Data Structures and Algorithms.- Strong programming skills in Python/Java/Scala/C/C++.- Strong problem solving and logical skills.- A go-getter kind of attitude with a willingness to learn new technologies.- Well versed with software design paradigms and good development practices.Responsibilities :- Developing novel algorithms and modeling techniques to advance the state of the art in Natural Language Processing.- Developing NLP based tools and solutions end to end.