xpressbees
http://www.xpressbees.comAbout
Jobs at xpressbees
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
XpressBees – a logistics company started in 2015 – is amongst the fastest growing
companies of its sector. While we started off rather humbly in the space of
ecommerce B2C logistics, the last 5 years have seen us steadily progress towards
expanding our presence. Our vision to evolve into a strong full-service logistics
organization reflects itself in our new lines of business like 3PL, B2B Xpress and cross
border operations. Our strong domain expertise and constant focus on meaningful
innovation have helped us rapidly evolve as the most trusted logistics partner of
India. We have progressively carved our way towards best-in-class technology
platforms, an extensive 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 improve efficiencies for our clients.
Job Profile
As a Lead Data Engineer in the Data Platform Team at XpressBees, you will build the data platform
and infrastructure to support high quality and agile decision-making in our supply chain and logistics
workflows.
You will define the way we collect and operationalize data (structured / unstructured), and
build production pipelines for our machine learning models, and (RT, NRT, Batch) reporting &
dashboarding requirements. As a Senior Data Engineer in the XB Data Platform Team, you will use
your experience with modern cloud and data frameworks to build products (with storage and serving
systems)
that drive optimisation and resilience in the supply chain via data visibility, intelligent decision making,
insights, anomaly detection and prediction.
What You Will Do
• Design and develop data platform and data pipelines for reporting, dashboarding and
machine learning models. These pipelines would productionize machine learning models
and integrate with agent review tools.
• Meet the data completeness, correction and freshness requirements.
• Evaluate and identify the data store and data streaming technology choices.
• Lead the design of the logical model and implement the physical model to support
business needs. Come up with logical and physical database design across platforms (MPP,
MR, Hive/PIG) which are optimal physical designs for different use cases (structured/semi
structured). Envision & implement the optimal data modelling, physical design,
performance optimization technique/approach required for the problem.
• Support your colleagues by reviewing code and designs.
• Diagnose and solve issues in our existing data pipelines and envision and build their
successors.
Qualifications & Experience relevant for the role
• A bachelor's degree in Computer Science or related field with 6 to 9 years of technology
experience.
• Knowledge of Relational and NoSQL data stores, stream processing and micro-batching to
make technology & design choices.
• Strong experience in System Integration, Application Development, ETL, Data-Platform
projects. Talented across technologies used in the enterprise space.
• Software development experience using:
• Expertise in relational and dimensional modelling
• Exposure across all the SDLC process
• Experience in cloud architecture (AWS)
• Proven track record in keeping existing technical skills and developing new ones, so that
you can make strong contributions to deep architecture discussions around systems and
applications in the cloud ( AWS).
• Characteristics of a forward thinker and self-starter that flourishes with new challenges
and adapts quickly to learning new knowledge
• Ability to work with a cross functional teams of consulting professionals across multiple
projects.
• Knack for helping an organization to understand application architectures and integration
approaches, to architect advanced cloud-based solutions, and to help launch the build-out
of those systems
• Passion for educating, training, designing, and building end-to-end systems.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
XpressBees– a logistics company started in 2015 – is amongst the fastest growing companies of its
sector. While we started off rather humbly in the space of ecommerce B2C logistics, the last 5 years
have seen us steadily progress towards expanding our presence. Our vision to evolve into a strong full-
service logistics organization reflects itself in our new lines of business like 3PL, B2B Xpress and cross
border operations.
Our strong domain expertise and constant focus on meaningful innovation have helped us rapidly evolve
as the most trusted logistics partner of India. We have progressively carved our way towards best-in-
class technology platforms, an extensive 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 improve efficiencies for our clients.
Job Description
XB is looking for driven & talented engineers to build highly scalable, reliable and performant cloud-
based platforms to drive the logistics business. You will have opportunities to make a big impact at XB
on the software solutions being built for Logistics businesses. We build a variety of technology products
that span multiple businesses.
The challenges that SDEs at XB solve are big (handle 50 Lakh shipments per day!) and influence the E-
Commerce business in India in coming years. We are looking for individuals who are passionate about
creating new products, features, and services from scratch while managing ambiguity and the fast pace
of the company. The challenges span areas like highly scalable and reliable orchestration
platforms, Client Integration API frameworks, Billing Solutions, Workforce Engagement. Further you may
solve complex optimization problems like Vehicle routing, Allocation, Network Optimization etc.
Roles & Responsibilities
You will be responsible for working with cross functional teams to deep dive into the
business and technology problems related to our portfolio of products, understanding the
gaps that exist in our current tools, and work within our team and with partner teams to
design best in class solutions.
You will have the opportunity to influence, invent, and design system architecture
across multiple product and technology spaces.
You will lead and mentor other talented engineers. You will be responsible for building
the best customer experience, keeping latency, security, and usability in mind.
You will interact with Product Managers and Designers and convert their vision into
a technical solution.
You will own portions of software deliverables including major critical path code from
your designs while finding opportunities to grow and mentor the team around you.
You will collaborate with other engineering leads and guide the team on software
development best practices and set examples by using them in solutions that you build.
You will own the end-to-end design of major deliverables, working closely with a team
of SDEs and Front-End Engineers to execute them. This is a high visibility and fast-paced
environment where you will make a direct impact on the customer experience and the
bottom line of the company.
You should have a commanding understanding of object-oriented design, data
structures and algorithms which you use to mentor a team of engineers. You should have
experience with agile methodologies, experience building scalable services and robust user
interfaces. We make extensive use of AWS Services (API Gateway, Lambda, SQS, etc.) and
prior experience is a plus. Experience with modern JavaScript frameworks (like angular,
react, backbone, and node.js) would be a plus.
Qualifications
Experience developing cloud software services and an understanding of design for
scalability, performance, and reliability.
Development experience defining, developing and maintaining web service API's
Demonstrated ability to mentor other software developers to maintain architectural
vision and software quality.
Experience in communicating with users, other technical teams, and senior
management to collect requirements, describe software product features, technical designs,
and product strategy.
Experience taking a leading role in building complex software systems that have been
successfully delivered to customers.
Knowledge of professional software engineering practices & best practices for the full
software development life cycle, including coding standards, code reviews, source control
management, build processes, testing, and operations.
Experience with distributed computing and enterprise-wide systems
Deep understanding of CS fundamentals including data structures, algorithms and
complexity analysis.
Experience building large-scale, high-performance systems in a complex, multi-tiered,
distributed environment.
Design and architecture expertise as well as familiarity with object-oriented analysis and
design patterns (OOA/OOD).
Ability to thrive in a fast-paced, dynamic environment.
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