Google ads specialist

Roles and responsibilities

Participate and contribute in design and development of the core components of the serviceto
Ensure high quality of software development with respect to architecture, code quality, testing and development
Implement testing frameworks and disciplines as part of every feature development
Own performance of app in production and implement / push for implementation of systems to monitor, debug and fix an issue in production in lowest TAT

Requirements
 
Who thrives in building applications at ease and speed and optimize the time and effort to build an application
Has good experience in building android applications
Experience with flutter eco system is a great plus
Who likes to think in terms of software and data architecture before opening android studio
Comfortable with managing development and deployment of applications
Open and more importantly excited about learning new technologies

JOB DESCRIPTION

It is an app that allows offline businesses to sell their products and services online. On our app, the users can make beautiful product catalogues (catalogs) right from a smartphone and share with their customers easily on different social media apps such as Whatsapp Business, Whatsapp, Facebook, Instagram etc. Praised by users all over India, thisapp has saved declining businesses by helping them transfer their shop online. The journey has just begun and we are on a mission to make India truly Digital. They are currently powering over 3.7 M ecommerce stores built by indian small businesses

and growing at a crazy rate.

 

We are looking for a full-stack developer to join our team who will be part of our new innovations team.

 

Responsibilities:

 

• Rapidly developing new user-facing features & product prototypes using React.js & Django.

• Will be responsible for new product prototypes, quick feature ideations & rapid response for critical issues

• Work on the their frontend store - Built with react & nextjs.
• Work on their backend - Built with Python Django & DRF
• Collaborate with existing team on our Android apps

 

Requirements:

• Familiarity with React & Next Js for frontend.
• Proficiency in backend development with Python Django & DRF
• Familiarity with Postgres, Elasticsearch & Mongo.
• Familiarity with Android app development with Native JAVA
• Familiarity with REST APIs architecture & working with third party APIs.

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.

If you are looking to be part of the early-stage start-up team that is charting the course and solving a key pain point for the CXO, this opportunity is for you. The opportunity will provide you join a company where you can contribute to all aspects of the product definition, product building and solving some key challenges.

• Architect solutions and execution through hands-on development, quality-assurance, and prototyping 
• Collaborate with a UX/UI designers and other front-end and middle-tier engineers to design, prototype, and build user interface for complex cloud-based product 
• Participate in complete development life cycle activities like design, coding, testing and production release 
• Develop and maintain a scalable web and responsive applications 
• Exhibit Devops mindset – Work on continuous integration, including provisioning, deployment, testing, and version control of the software 
• Mentor new software developers and junior engineers

• Passionate engineer with 5 – 8 years of hands-on experience of developing next-generation user interface with high quality and performance 
• Strong desire to learn & evaluate new libraries/frameworks, and share knowledge with others 
• Ability to work in a fast-paced and agile development environment 
• Sound knowledge of front end standards and practices 
• Translating designs and wireframes into high-quality code 
• Knowledge of Redux, React.js and its core principles 
• Familiarity with RESTful APIs 
• Strong proficiency in JavaScript, AJAX, HTML5, CSS3, JSON, including DOM manipulation and the JavaScript object model 
• Experience with popular JS frameworks and libraries (React, Angular, JQuery, Ember, Babel, Webpack etc.) 
• Experience of building Single-page Web Apps 
• Ability to understand business requirements and translate them into technical requirements 
• Experience with test automation: TDD, unit/integration/functional testing 
• Proficient with debugging and testing tools to troubleshoot and optimize the UI 
• Solid understanding of object-oriented design and programming concepts, core JavaScript concepts like scope/closures, the event loop and asynchronous callbacks, promises

Good to have

• Full-stack development experience 
• Prior Startup Experience 
• Prior experience in developing real-time web applications 
• Experience with continuous deployment 
• Proficiency with Git/Github 
• Experience with GraphQL

Success Factors

• Start-up mindset 
• Good problem solving abilities 
• ‘Can-do’ attitude 
• Prior experience of working with globally distributed teams is an added advantage 
• Work with minimal supervision 
• Excellent communication skills and being able to work independently or in a full team