AI/ML Developer

Required Skills
Experience with various stream processing and batch processing tools (Kafka,
Spark etc). Programming with Python.
● Experience with relational and non-relational databases.
● Fairly good understanding of AWS (or any equivalent).


Key Responsibilities
● Design new systems and redesign existing systems to work at scale.
● Care about things like fault tolerance, durability, backups and recovery,
performance, maintainability, code simplicity etc.
● Lead a team of software engineers and help create an environment of ownership
and learning.
● Introduce best practices of software development and ensure their adoption
across the team.
● Help set and maintain coding standards for the team.

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

Position : Data Engineer

Duration : Full Time

Location : Vishakhapatnam, Bangalore, Chennai

years of experience : 3+ years

Job Description :

- 3+ Years of working as a Data Engineer with thorough understanding of data frameworks that collect, manage, transform and store data that can derive business insights.

- Strong communications (written and verbal) along with being a good team player.

- 2+ years of experience within the Big Data ecosystem (Hadoop, Sqoop, Hive, Spark, Pig, etc.)

- 2+ years of strong experience with SQL and Python (Data Engineering focused).

- Experience with GCP Data Services such as BigQuery, Dataflow, Dataproc, etc. is an added advantage and preferred.

- Any prior experience in ETL tools such as DataStage, Informatica, DBT, Talend, etc. is an added advantage for the role.

Technical Knowledge (Must Have)

• Strong experience in SQL / HiveQL/ AWS Athena,
• Strong expertise in the development of data pipelines (snaplogic is preferred).
• Design, Development, Deployment and administration of data processing applications.
• Good Exposure towards AWS and Azure Cloud computing environments.
• Knowledge around BigData, AWS Cloud Architecture, Best practices, Securities, Governance, Metadata Management, Data Quality etc.
• Data extraction through various firm sources (RDBMS, Unstructured Data Sources) and load to datalake with all best practices.
• Knowledge in Python
• Good knowledge in NoSQL technologies (Neo4J/ MongoDB)
• Experience/knowledge in SnapLogic (ETL Technologies)
• Working knowledge on Unix (AIX, Linux), shell scripting
• Experience/knowledge in Data Modeling. Database Development
• Experience/knowledge creation of reports and dashboards in Tableau/ PowerBI

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.

Job Description

• Design, development and deployment of highly-available and fault-tolerant enterprise business software at scale.

• Demonstrate tech expertise to go very deep or broad in solving classes of problems or creating broadly leverage-able solutions.

• Execute large-scale projects - Provide technical leadership in architecting and building product solutions.

• Collaborate across teams to deliver a result, from hardworking team members within your group, through smart technologists across lines of business.

• Be a role model on acting with good judgment and responsibility, helping teams to commit and move forward.

• Be a humble mentor and trusted advisor for both our talented team members and passionate leaders alike. Deal with differences in opinion in a mature and fair way.

• Raise the bar by improving standard methodologies, producing best-in-class efficient solutions, code, documentation, testing, and monitoring.

Qualifications

      • 15+ years of relevant engineering experience.

• Proven record of building and productionizing highly reliable products at scale.

• Experience with Java and Python

• Experience with the Big Data technologie is a plus.

• Ability to assess new technologies and make pragmatic choices that help guide us towards a long-term vision

• Can collaborate well with several other engineering orgs to articulate requirements and system design

Additional Information

Professional Attributes:
• Team player!

• Great interpersonal skills, deep technical ability, and a portfolio of successful execution.

• Excellent written and verbal communication skills, including the ability to write detailed technical documents.

• Passionate about helping teams grow by inspiring and mentoring engineers.

Data science Freshers with a Product & IT service based company

Qualifications
B.Tech/M.Tech
Percentage 70% and above
2018 & 2019 passouts
At least 3 POC Implementations should have done
Premium Institutes passouts are more preferrable

• Desire to explore new technology and break new ground.
• Are passionate about Open Source technology, continuous learning, and innovation.
• Have the problem-solving skills, grit, and commitment to complete challenging work assignments and meet deadlines.

Qualifications

• Engineer enterprise-class, large-scale deployments, and deliver Cloud-based Serverless solutions to our customers.
• You will work in a fast-paced environment with leading microservice and cloud technologies, and continue to develop your all-around technical skills.
• Participate in code reviews and provide meaningful feedback to other team members.
• Create technical documentation.
• Develop thorough Unit Tests to ensure code quality.

Skills and Experience

• Advanced skills in troubleshooting and tuning AWS Lambda functions developed with Java and/or Python.
• Experience with event-driven architecture design patterns and practices
• Experience in database design and architecture principles and strong SQL abilities
• Message brokers like Kafka and Kinesis
• Experience with Hadoop, Hive, and Spark (either PySpark or Scala)
• Demonstrated experience owning enterprise-class applications and delivering highly available distributed, fault-tolerant, globally accessible services at scale.
• Good understanding of distributed systems.
• Candidates will be self-motivated and display initiative, ownership, and flexibility.

 

Preferred Qualifications

• AWS Lambda function development experience with Java and/or Python.
• Lambda triggers such as SNS, SES, or cron.
• Databricks
• Cloud development experience with AWS services, including:
• IAM
• S3
• EC2
• AWS CLI
• API Gateway
• ECR
• CloudWatch
• Glue
• Kinesis
• DynamoDB
• Java 8 or higher
• ETL data pipeline building
• Data Lake Experience
• Python
• Docker
• MongoDB or similar NoSQL DB.
• Relational Databases (e.g., MySQL, PostgreSQL, Oracle, etc.).
• Gradle and/or Maven.
• JUnit
• Git
• Scrum
• Experience with Unix and/or macOS.
• Immediate Joiners

Nice to have:

• AWS / GCP / Azure Certification.
• Cloud development experience with Google Cloud or Azure