Primary Responsibilities: Develop solutions using big data technologies and AWS services on AWS cloud.
Hands-on experience in AWS services (S3, AWS Lambda, Athena, Step functions, AWS Glue, Kinesis, AWS DynamoDB (AWS Serverless Technologies), Fargate, ECS, Load Balancers, Cloudwatch, EMR etc.)
Hands-on experience in Big Data (Hadoop, Spark, Hive, HDFS, Kafka, Zookeeper etc.)
Hands-on experience in programming (Python, Pyspark, Scala)
Experience in creating data pipelines – ingestion, processing and orchestration.
Experience working within a Linux computing environment, and use of command line tools including knowledge of scripting for automating common tasks.
Understanding about data engineering concepts (near-/real-time streaming, data structures, metadata and workflow management).
Challenges involved in Big Data – large data sizes (e.g. depth/width), even distribution of data
Apply advanced troubleshooting techniques to provide Solutions to issues pertaining to Service Availability, Performance, and Resiliency
Monitor & Optimize the performance using AWS dashboards and logs. Partner with Engineering leaders and peers in delivering technology solutions that meet the business requirements.
AWS certification would be preferred
2+ years good experience with AWS services: S3, AWS Lambda, Athena, Step functions, AWS Glue, Kinesis, ECS, AWS DynamoDB (AWS Serverless Technologies), Fargate, Load Balancers, Cloudwatch, EMR.
2+ years good experience working with Bigdata technologies: Hadoop, Spark, Hive, HDFS, Kafka, Zookeeper.
Good experience in data structure, programming in (pyspark / python / golang / Scala)
We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.
- 5+ years deploying Machine Learning pipelines in large enterprise production systems.
- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.
Roles and Responsibilities:
Deploying ML models into production, and scaling them to serve millions of customers.
Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.
Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.
Provide software design and programming support to projects.
Qualifications & Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.
|Job Title: Data Engineer|
|Tech Job Family: DACI|
|• Bachelor's Degree in Engineering, Computer Science, CIS, or related field (or equivalent work experience in a related field)|
|• 2 years of experience in Data, BI or Platform Engineering, Data Warehousing/ETL, or Software Engineering|
|• 1 year of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC)|
|• Master's Degree in Computer Science, CIS, or related field|
|• 2 years of IT experience developing and implementing business systems within an organization|
|• 4 years of experience working with defect or incident tracking software|
|• 4 years of experience with technical documentation in a software development environment|
|• 2 years of experience working with an IT Infrastructure Library (ITIL) framework|
|• 2 years of experience leading teams, with or without direct reports|
|• Experience with application and integration middleware|
|• Experience with database technologies|
|• 2 years of experience in Hadoop or any Cloud Bigdata components (specific to the Data Engineering role)|
|• Expertise in Java/Scala/Python, SQL, Scripting, Teradata, Hadoop (Sqoop, Hive, Pig, Map Reduce), Spark (Spark Streaming, MLib), Kafka or equivalent Cloud Bigdata components (specific to the Data Engineering role)|
|• Expertise in MicroStrategy/Power BI/SQL, Scripting, Teradata or equivalent RDBMS, Hadoop (OLAP on Hadoop), Dashboard development, Mobile development (specific to the BI Engineering role)|
|• 2 years of experience in Hadoop, NO-SQL, RDBMS or any Cloud Bigdata components, Teradata, MicroStrategy (specific to the Platform Engineering role)|
|• Expertise in Python, SQL, Scripting, Teradata, Hadoop utilities like Sqoop, Hive, Pig, Map Reduce, Spark, Ambari, Ranger, Kafka or equivalent Cloud Bigdata components (specific to the Platform Engineering role)|
|Lowe’s is an equal opportunity employer and administers all personnel practices without regard to race, color, religion, sex, age, national origin, disability, sexual orientation, gender identity or expression, marital status, veteran status, genetics or any other category protected under applicable law.|
We are looking for an exceptional Software Developer for our Data Engineering India team who can-
contribute to building a world-class big data engineering stack that will be used to fuel us
Analytics and Machine Learning products. This person will be contributing to the architecture,
operation, and enhancement of:
Our petabyte-scale data platform with a key focus on finding solutions that can support
Analytics and Machine Learning product roadmap. Everyday terabytes of ingested data
need to be processed and made available for querying and insights extraction for
various use cases.
About the Organisation:
- It provides a dynamic, fun workplace filled with passionate individuals. We are at the cutting edge of advertising technology and there is never a dull moment at work.
- We have a truly global footprint, with our headquarters in Singapore and offices in Australia, United States, Germany, United Kingdom, and India.
- You will gain work experience in a global environment. We speak over 20 different languages, from more than 16 different nationalities and over 42% of our staff are multilingual.
Software Developer, Data Engineering team
Location: Pune(Initially 100% Remote due to Covid 19 for coming 1 year)
contribute to the prototyping, building, and deployment of Machine Learning models.
Spark, Flume, Hive, Druid etc… while at the same time understanding that certain
problems may require completely novel solutions.
GCP ML Stack, AWS Sagemaker - is a plus.
warehouses, big data analytics platforms, and high velocity data pipelines
**** Not looking for a Big Data Developer / Hadoop Developer
Position Name: Software Developer
Required Experience: 3+ Years
Number of positions: 4
Qualifications: Master’s or Bachelor s degree in Engineering, Computer Science, or equivalent (BE/BTech or MS in Computer Science).
Key Skills: Python, Django, Ngnix, Linux, Sanic, Pandas, Numpy, Snowflake, SciPy, Data Visualization, RedShift, BigData, Charting
Compensation - As per industry standards.
Joining - Immediate joining is preferrable.
Reval Analytical Services is a fully-owned subsidiary of Virtua Research Inc. US. It is a financial services technology company focused on consensus analytics, peer analytics and Web-enabled information delivery. The Company’s unique combination of investment research experience, modeling expertise, and software development capabilities enables it to provide industry-leading financial research tools and services for investors, analysts, and corporate management.
GREETINGS FROM CODEMANTRA !!!
EXCELLENT OPPORTUNITY FOR DATA SCIENCE/AI AND ML ARCHITECT !!!
Skills and Qualifications
*Strong Hands-on experience in Python Programming
*** Working experience with Computer Vision models - Object Detection Model, Image Classification
* Good experience in feature extraction, feature selection techniques and transfer learning
* Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.
* Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.
* Good experience in exploratory data analysis, data visualisation, and other data pre-processing techniques.
* Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe Good knowledge in statistics, distribution of data and in supervised and unsupervised machine learning algorithms.
* Exposure to OpenCV Familiarity with GPUs + CUDA Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.
* We are looking for a candidate with 9+ years of relevant experience , who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: *Experience with big data tools: Hadoop, Spark, Kafka, etc.
*Experience with AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
*Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.
*Selecting features, building and optimizing classifiers using machine learning techniques
*Data mining using state-of-the-art methods
*Enhancing data collection procedures to include information that is relevant for building analytic systems
*Processing, cleansing, and verifying the integrity of data used for analysis
*Creating automated anomaly detection systems and constant tracking of its performance
*Assemble large, complex data sets that meet functional / non-functional business requirements.
*Secure and manage when needed GPU cluster resources for events
*Write comprehensive internal feedback reports and find opportunities for improvements
*Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model