Applied Machine Learning Engineer

Greetings!!

We are looking out for a technically driven  "ML OPS Engineer" for one of our premium client

COMPANY DESCRIPTION:


Key Skills
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)

Job Description – Data Science  

 

Basic Qualification:

• ME/MS from premier institute with a background in Mechanical/Industrial/Chemical/Materials engineering.
• Strong Analytical skills and application of Statistical techniques to problem solving
• Expertise in algorithms, data structures and performance optimization techniques
• Proven track record of demonstrating end to end ownership involving taking an idea from incubator to market
•   Minimum years of experience in data analysis (2+), statistical analysis, data mining, algorithms for optimization.

Responsibilities

The Data Engineer/Analyst will

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  
• Clear interaction with Business teams including product planning, sales, marketing, finance for defining the projects, objectives.
  
• Mine and analyze data from company databases to drive optimization and improvement of product and process development, marketing techniques and business strategies
  
• Coordinate with different R&D and Business teams to implement models and monitor outcomes.
  
• Mentor team members towards developing quick solutions for business impact.
  
• Skilled at all stages of the analysis process including defining key business questions, recommending measures, data sources, methodology and study design, dataset creation, analysis execution, interpretation and presentation and publication of results.
  

 

• 4+ years’ experience in MNC environment with projects involving ML, DL and/or DS
  
• Experience in Machine Learning, Data Mining or Machine Intelligence (Artificial Intelligence)
  
• Knowledge on Microsoft Azure will be desired.
  
• Expertise in machine learning such as Classification, Data/Text Mining, NLP, Image Processing, Decision Trees, Random Forest, Neural Networks, Deep Learning Algorithms
  
• Proficient in Python and its various libraries such as Numpy, MatPlotLib, Pandas
  
• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to Business Teams.
  
• Experience in infra development / building platforms is highly desired.
  
• A drive to learn and master new technologies and techniques.
  

Carsome’s Data Department is on the lookout for a Data Scientist/Data Science Lead who has a strong passion in building data powered products.

 

Data Science function under the Data Department has a responsibility for standardisation of methods, mentoring team of data science resources/interns, including code libraries and documentation, quality assurance of outputs, modeling techniques and statistics, leveraging a variety of technologies, open-source languages, and cloud computing platform. 

 

You will get to lead & implement projects such as price optimization/prediction, enabling iconic personalization experiences for our customer, inventory optimization etc.

 

Job Descriptions

 

• Identifying and integrating datasets that can be leveraged through our product and work closely with data engineering team to develop data products.
• Execute analytical experiments methodically to help solve various problems and make a true impact across functions such as operations, finance, logistics, marketing. 
• Identify, prioritize, and design testing opportunities that will inform algorithm enhancements. 
• Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models and clean and validate data for uniformity and accuracy.
• Unlock insights by analyzing large amounts of complex website traffic and transactional data. 
• Implement analytical models into production by collaborating with data analytics engineers.

 

Technical Requirements

 

• Expertise in model design, training, evaluation, and implementation ML Algorithm expertise K-nearest neighbors, Random Forests, Naive Bayes, Regression Models. PyTorch, TensorFlow, Keras, deep learning expertise, tSNE, gradient boosting expertise, regression implementation expertise, Python, Pyspark, SQL, R, AWS Sagemaker /personalize etc.
• Machine Learning / Data Science Certification

 

Experience & Education 

 

• Bachelor’s in Engineering / Master’s in Data Science  / Postgraduate Certificate in Data Science. 

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.

Day-to-day responsibilities include:

1. Working on supervised and unsupervised learning algorithms
2. Developing deep learning and machine learning algorithms
3. Working on live projects on data analytics

About Vedantu --------------------------- If you have ever dreamed about being in the driver’s seat of a revolution, THIS is the place for you. Vedantu is an Ed-Tech startup which is into Live Online Tutoring. Recently raised Series B funding of $11M Job Description We are looking for a Data Scientist who will support our product, sales, leadership and marketing teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product, sales and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data analysis methods, building and implementing models and using/creating appropriate algorithms. Desired Skills 1. Experience using statistical computer languages (R, Python,etc.) to manipulate data and draw insights from large data sets. 2. Process, cleanse, and verify the integrity of data used for analysis. 3. Comfortable manipulating and analyzing complex, high-volume, high-dimensionality data from varying, heterogeneous sources 4. Experience with messy real-world data -- handling missing/incomplete/inaccurate data 5. Understanding of a broad set of Algorithms and Applied Math. 6. Good at problem solving, probability and statistics and knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage) and experience with applications. 7. Knowledge of data scraping is preferable 8. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their real-world advantages/drawbacks. 9. Experience with big data tools (Hadoop, Hive, MapReduce) a plus.

Job Description: Be responsible for scaling our analytics capability across all internal disciplines and guide our strategic direction in regards to analytics Organize and analyze large, diverse data sets across multiple platforms Identify key insights and leverage them to inform and influence product strategy Technical Interactions with vendor or partners in technical capacity for scope/ approach & deliverables. Develops proof of concept to prove or disprove validity of concept. Working with all parts of the business to identify analytical requirements and formalize an approach for reliable, relevant, accurate, efficientreporting on those requirements Designing and implementing advanced statistical testing for customized problem solving Deliver concise verbal and written explanations of analyses to senior management that elevate findings into strategic recommendations Desired Candidate Profile: MTech / BE / BTech / MSc in CS or Stats or Maths, Operation Research, Statistics, Econometrics or in any quantitative field Experience in using Python, R, SAS Experience in working with large data sets and big data systems (SQL, Hadoop, Hive, etc.) Keen aptitude for large-scale data analysis with a passion for identifying key insights from data Expert working knowledge in various machine learning algorithms such XGBoost, SVM Etc. We are looking candidates from the following: Experience in Unsecured Loans & SME Loans analytics (cards, installment loans) - risk based pricing analytics Experience in Differential pricing / selection analytics (retail, airlines / travel etc). Experience in Digital product companies or Digital eCommerce with Product mindset and experience Experience in Fraud / Risk from Banks, NBFC / Fintech / Credit Bureau Experience in Online media with knowledge of media, online ads & sales (agencies) - Knowledge of DMP, DFP, Adobe/Omniture tools, Cloud Experience in Consumer Durable Loans lending companies (Experience in Credit Cards, Personal Loan - optional) Experience in Tractor Loans lending companies (Experience in Farm) Experience in Recovery, Collections analytics Experience in Marketing Analytics with Digital Marketing, Market Mix modelling, Advertising Technology

About the Company:

This opportunity is for an AI Drone Technology startup funded by the Indian Army. It is working to develop cutting-edge products to help the Indian Army gain an edge in New Age Enemy Warfare.

They are working on using drones to neutralize terrorists hidden in deep forests. Get a chance to contribute to secure our borders against the enemy.

Responsibilities:

• Extensive knowledge in machine learning and deep learning techniques
• Solid background in image processing/computer vision
• Experience in building datasets for computer vision tasks
• Experience working with and creating data structures/architectures
• Proficiency in at least one major machine learning framework such as Tensorflow, Pytorch
• Experience visualizing data to stakeholders
• Ability to analyze and debug complex algorithms
• Highly skilled in Python scripting language
• Creativity and curiosity for solving highly complex problems
• Excellent communication and collaboration skills

 

Educational Qualification:

MS in Engineering, Applied Mathematics, Data Science, Computer Science or equivalent field, with 3 years industry experience, a PhD degree or equivalent industry experience.

About us
DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.

Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.

How we work?
It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!

What do we offer?
- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!
- Ability to see the impact of your work and the value you're adding to our customers almost immediately.
- Opportunity to work on different problems and explore a wide variety of tools to figure out what really excites you.
- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.
- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
- Last but not the least, competitive salary packages and fast paced growth opportunities.

Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities.

We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).

Key problem areas
- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.
- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.
- Ensemble approaches for all the above problems using multiple text and image based techniques.

Relevant set of skills
- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.
- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.
- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.
- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.
- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.
- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.

Role and responsibilities
- Understand the business problems we are solving. Build data science capability that align with our product strategy.
- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
- Build robust clustering and classification models in an iterative manner that can be used in production.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Take end to end ownership of the projects you are working on. Work with minimal supervision.
- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.

-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.