Engineering - Lead / Manager

Responsibilities: 

• Write user-focused content that explains how to use different product features. 
• Develop engaging technical content for developer wikis, user guides, integration guides, and how-tos. 

• Fine-tune and prepare content to appeal to non-technical end-users, programmers, system administrators, designers, and analysts. 
• Develop and oversee illustrative material, flowcharts, examples, and tutorials that show how to use software features on the company platform. 
• Actively participate in developing scalable documentation strategy, policy, and guidelines. 
• Analyze documents to enhance the accuracy, completeness, and relevance of content and maintain continuity of style. 

Requirements 

• Experience as a technical writer, editor, or content strategist, with a focus on software and workflow applications. 
• Adept in creating bovr-to guides, user guides, and wikis with extraordinary presentation skills. Transform complex concepts into clear, concise, and meaningful topics - simplicity is the key. 
• Work closely with cross-functional teams to identify and close documentation gaps. 
• Experience with Atlassian tools or Click Up. 
• Strong technology fundamentals: We expect you to go from the highest level of abstraction to

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.

1.Testing & Validation of new products developed
2.Work with R&D/Product team & suggest new ideas/product improvement areas
3.Work with customers for installation of products
4.Technical support at customer location
BE/B.Tech (Electronics & Communication) or 3 years Diploma in Electronics & Communication

0-1 year for BE/B.Tech OR
3 to 5 years for Diploma holder testing any electronics products

We are looking for a React Native developer interested in building performant mobile apps on both the iOS and Android platforms. You will be responsible for architecting and building these applications, as well as coordinating with the teams responsible for other layers of the product infrastructure. Building a product is a highly collaborative effort, and as such, a strong team player with a commitment to perfection is required.

Responsibilities

• Build pixel-perfect, buttery smooth UIs across both mobile platforms.
• Leverage native APIs for deep integrations with both platforms.
• Diagnose and fix bugs and performance bottlenecks for performance that feels native.
• Reach out to the open source community to encourage and help implement mission-critical software fixesReact Native moves fast and often breaks things.
• Maintain code and write automated tests to ensure the product is of the highest quality.
• Transition existing React web apps to React Native

 

Hello Everyone!

On behalf of one of our clients,we are hiring Tester / QA Executive.
Responsibilities

• Review requirements, specifications and technical design documents to provide timely and meaningful feedback
• Create detailed, comprehensive and well-structured test plans and test cases
• Estimate, prioritize, plan and coordinate testing activities
• Design, develop and execute automation scripts using open source tools
• Identify, record, document thoroughly and track bugs
• Perform thorough regression testing when bugs are resolved
• Develop and apply testing processes for new and existing products to meet client needs
• Liaise with internal teams (e.g. developers and product managers) to identify system requirements
• Monitor debugging process results
• Investigate the causes of non-conforming software and train users to implement solutions
• Track quality assurance metrics, like defect densities and open defect counts
• Stay up-to-date with new testing tools and test strategies

Skills Requirements

• Proven work experience in software development
• Proven work experience in software quality assurance
• Strong knowledge of software QA methodologies, tools and processes
• Experience in writing clear, concise and comprehensive test plans and test cases
• Hands-on experience with both white box and black box testing
• Hands-on experience with automated testing tools
• Solid knowledge of SQL and scripting
• Experience working in an Agile/Scrum development process
• Experience with performance and/or security testing is a plus
• Tech in IT

Looking for highly motivated webmethods integrations developers with experience in advanced database concepts and Java to be part of an energetic and vibrant Integrations platform. We are looking for engineers with 6 plus years of experience with strong communication skills and Ability to work independently and also be an effective team player.

Talent Acquisition Specialist: Are you a passionate recruiter with a go getter attitude and ready to explore the Talent Acquisition space for the new age tech? We have an opportunity for you! Job Responsibilities include: Collaborate closely with hiring managers to adequately understand the needs of the manager and the requirements and expectations of the job. Must source and recruit candidates using a variety of outlets, such as job postings and social media, while effectively targeting the right kinds of candidates for the job. Throughout this process, develop relationships with prospective talent. Seek out and recommend creative new ways of sourcing talent. Schedule all interviews and then prepare and advise their candidates beforehand. Review resumes, cover letters, and assess interview performance. In order to facilitate a smooth on-boarding process for new employees, administer and submit all hiring paperwork for new employees as well as assist with the orientation process. Maintain awareness of competitor practices, industry trends and recruitment standards. Must complete all pre-screening and screening activities for prospective employees, which may include calling previous employers and completing background screens. Document interactions, outreach, and screening results as well as staffing metrics. Conceptualize and implement various recruitment strategies to effectively close all the positions. Streamline the usage of ATS Qualifications required: Bachelor's Degree 3 to 4 years of experience in handling end to end recruitment Hands on experience in working on Big Data and Machine Learning skills for a minimum of 1 year is a must. Excellent communication(oral and written) skills and ability to provide a pleasant experience for the candidates Motivated, proactive and well organised to handle end ot end process Experience using the ATS Proven success in position closures according to the TAT. Passion to go above and beyond the set goal Familiartly using G Suite will be preferred.