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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.
Skills:
- 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.
Top Management Consulting Company
We are looking out for a technically driven "ML OPS Engineer" for one of our premium client
COMPANY DESCRIPTION:
Key Skills
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)
5-7 years of experience in Data Engineering with solid experience in design, development and implementation of end-to-end data ingestion and data processing system in AWS platform.
2-3 years of experience in AWS Glue, Lambda, Appflow, EventBridge, Python, PySpark, Lake House, S3, Redshift, Postgres, API Gateway, CloudFormation, Kinesis, Athena, KMS, IAM.
Experience in modern data architecture, Lake House, Enterprise Data Lake, Data Warehouse, API interfaces, solution patterns, standards and optimizing data ingestion.
Experience in build of data pipelines from source systems like SAP Concur, Veeva Vault, Azure Cost, various social media platforms or similar source systems.
Expertise in analyzing source data and designing a robust and scalable data ingestion framework and pipelines adhering to client Enterprise Data Architecture guidelines.
Proficient in design and development of solutions for real-time (or near real time) stream data processing as well as batch processing on the AWS platform.
Work closely with business analysts, data architects, data engineers, and data analysts to ensure that the data ingestion solutions meet the needs of the business.
Troubleshoot and provide support for issues related to data quality and data ingestion solutions. This may involve debugging data pipeline processes, optimizing queries, or troubleshooting application performance issues.
Experience in working in Agile/Scrum methodologies, CI/CD tools and practices, coding standards, code reviews, source management (GITHUB), JIRA, JIRA Xray and Confluence.
Experience or exposure to design and development using Full Stack tools.
Strong analytical and problem-solving skills, excellent communication (written and oral), and interpersonal skills.
Bachelor's or master's degree in computer science or related field.
Design, implement, and improve the analytics platform
Implement and simplify self-service data query and analysis capabilities of the BI platform
Develop and improve the current BI architecture, emphasizing data security, data quality
and timeliness, scalability, and extensibility
Deploy and use various big data technologies and run pilots to design low latency
data architectures at scale
Collaborate with business analysts, data scientists, product managers, software development engineers,
and other BI teams to develop, implement, and validate KPIs, statistical analyses, data profiling, prediction,
forecasting, clustering, and machine learning algorithms
Educational
At Ganit we are building an elite team, ergo we are seeking candidates who possess the
following backgrounds:
7+ years relevant experience
Expert level skills writing and optimizing complex SQL
Knowledge of data warehousing concepts
Experience in data mining, profiling, and analysis
Experience with complex data modelling, ETL design, and using large databases
in a business environment
Proficiency with Linux command line and systems administration
Experience with languages like Python/Java/Scala
Experience with Big Data technologies such as Hive/Spark
Proven ability to develop unconventional solutions, sees opportunities to
innovate and leads the way
Good experience of working in cloud platforms like AWS, GCP & Azure. Having worked on
projects involving creation of data lake or data warehouse
Excellent verbal and written communication.
Proven interpersonal skills and ability to convey key insights from complex analyses in
summarized business terms. Ability to effectively communicate with multiple teams
Good to have
AWS/GCP/Azure Data Engineer Certification
Job Sector: IT, Software
Job Type: Permanent
Location: Chennai
Experience: 10 - 20 Years
Salary: 12 – 40 LPA
Education: Any Graduate
Notice Period: Immediate
Key Skills: Python, Spark, AWS, SQL, PySpark
Contact at triple eight two zero nine four two double seven
Job Description:
Requirements
- Minimum 12 years experience
- In depth understanding and knowledge on distributed computing with spark.
- Deep understanding of Spark Architecture and internals
- Proven experience in data ingestion, data integration and data analytics with spark, preferably PySpark.
- Expertise in ETL processes, data warehousing and data lakes.
- Hands on with python for Big data and analytics.
- Hands on in agile scrum model is an added advantage.
- Knowledge on CI/CD and orchestration tools is desirable.
- AWS S3, Redshift, Lambda knowledge is preferred
Analytics Job Description
We are hiring an Analytics Engineer to help drive our Business Intelligence efforts. You will
partner closely with leaders across the organization, working together to understand the how
and why of people, team and company challenges, workflows and culture. The team is
responsible for delivering data and insights that drive decision-making, execution, and
investments for our product initiatives.
You will work cross-functionally with product, marketing, sales, engineering, finance, and our
customer-facing teams enabling them with data and narratives about the customer journey.
You’ll also work closely with other data teams, such as data engineering and product analytics,
to ensure we are creating a strong data culture at Blend that enables our cross-functional partners
to be more data-informed.
Role : DataEngineer
Please find below the JD for the DataEngineer Role..
Location: Guindy,Chennai
How you’ll contribute:
• Develop objectives and metrics, ensure priorities are data-driven, and balance short-
term and long-term goals
• Develop deep analytical insights to inform and influence product roadmaps and
business decisions and help improve the consumer experience
• Work closely with GTM and supporting operations teams to author and develop core
data sets that empower analyses
• Deeply understand the business and proactively spot risks and opportunities
• Develop dashboards and define metrics that drive key business decisions
• Build and maintain scalable ETL pipelines via solutions such as Fivetran, Hightouch,
and Workato
• Design our Analytics and Business Intelligence architecture, assessing and
implementing new technologies that fitting
• Work with our engineering teams to continually make our data pipelines and tooling
more resilient
Who you are:
• Bachelor’s degree or equivalent required from an accredited institution with a
quantitative focus such as Economics, Operations Research, Statistics, Computer Science OR 1-3 Years of Experience as a Data Analyst, Data Engineer, Data Scientist
• Must have strong SQL and data modeling skills, with experience applying skills to
thoughtfully create data models in a warehouse environment.
• A proven track record of using analysis to drive key decisions and influence change
• Strong storyteller and ability to communicate effectively with managers and
executives
• Demonstrated ability to define metrics for product areas, understand the right
questions to ask and push back on stakeholders in the face of ambiguous, complex
problems, and work with diverse teams with different goals
• A passion for documentation.
• A solution-oriented growth mindset. You’ll need to be a self-starter and thrive in a
dynamic environment.
• A bias towards communication and collaboration with business and technical
stakeholders.
• Quantitative rigor and systems thinking.
• Prior startup experience is preferred, but not required.
• Interest or experience in machine learning techniques (such as clustering, decision
tree, and segmentation)
• Familiarity with a scientific computing language, such as Python, for data wrangling
and statistical analysis
• Experience with a SQL focused data transformation framework such as dbt
• Experience with a Business Intelligence Tool such as Mode/Tableau
Mandatory Skillset:
-Very Strong in SQL
-Spark OR pyspark OR Python
-Shell Scripting
A leading global information technology and business process
Python + Data scientist : |
• Build data-driven models to understand the characteristics of engineering systems |
• Train, tune, validate, and monitor predictive models |
• Sound knowledge on Statistics |
• Experience in developing data processing tasks using PySpark such as reading, merging, enrichment, loading of data from external systems to target data destinations |
• Working knowledge on Big Data or/and Hadoop environments |
• Experience creating CI/CD Pipelines using Jenkins or like tools |
• Practiced in eXtreme Programming (XP) disciplines |
Role Summary/Purpose:
We are looking for a Developer/Senior Developers to be a part of building advanced analytical platform leveraging Big Data technologies and transform the legacy systems. This role is an exciting, fast-paced, constantly changing and challenging work environment, and will play an important role in resolving and influencing high-level decisions.
Requirements:
- The candidate must be a self-starter, who can work under general guidelines in a fast-spaced environment.
- Overall minimum of 4 to 8 year of software development experience and 2 years in Data Warehousing domain knowledge
- Must have 3 years of hands-on working knowledge on Big Data technologies such as Hadoop, Hive, Hbase, Spark, Kafka, Spark Streaming, SCALA etc…
- Excellent knowledge in SQL & Linux Shell scripting
- Bachelors/Master’s/Engineering Degree from a well-reputed university.
- Strong communication, Interpersonal, Learning and organizing skills matched with the ability to manage stress, Time, and People effectively
- Proven experience in co-ordination of many dependencies and multiple demanding stakeholders in a complex, large-scale deployment environment
- Ability to manage a diverse and challenging stakeholder community
- Diverse knowledge and experience of working on Agile Deliveries and Scrum teams.
Responsibilities
- Should works as a senior developer/individual contributor based on situations
- Should be part of SCRUM discussions and to take requirements
- Adhere to SCRUM timeline and deliver accordingly
- Participate in a team environment for the design, development and implementation
- Should take L3 activities on need basis
- Prepare Unit/SIT/UAT testcase and log the results
- Co-ordinate SIT and UAT Testing. Take feedbacks and provide necessary remediation/recommendation in time.
- Quality delivery and automation should be a top priority
- Co-ordinate change and deployment in time
- Should create healthy harmony within the team
- Owns interaction points with members of core team (e.g.BA team, Testing and business team) and any other relevant stakeholders
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.
Responsibilities
*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
Regards
Ranjith PR