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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.

• A Natural Language Processing (NLP) expert with strong computer science fundamentals and experience in working with deep learning frameworks. You will be working at the cutting edge of NLP and Machine Learning.

Roles and Responsibilities

• Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.
• Mentor and coach other team members
• Evaluate the performance of NLP models and ideate on how they can be improved
• Support internal and external NLP-facing APIs
• Keep up to date on current research around NLP, Machine Learning and Deep Learning

Mandatory Requirements

• Any graduation with at least 2 years of demonstrated experience as a Data Scientist.

Behavioral Skills

Strong analytical and problem-solving capabilities.

• Proven ability to multi-task and deliver results within tight time frames
• Must have strong verbal and written communication skills
• Strong listening skills and eagerness to learn
• Strong attention to detail and the ability to work efficiently in a team as well as individually

Technical Skills

Hands-on experience with

• NLP
• Deep Learning
• Machine Learning
• Python
• Bert

Preferred Requirements

• Experience in Computer Vision is preferred

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

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

AWS Glue Developer 

Work Experience: 6 to 8 Years

Work Location:  Noida, Bangalore, Chennai & Hyderabad

Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops, 

Job Reference ID:BT/F21/IND

Job Description:

Design, build and configure applications to meet business process and application requirements.

Responsibilities:

7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.

Technical Experience:

Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.

➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.

➢ Create data pipeline architecture by designing and implementing data ingestion solutions.

➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.

➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.

➢ Author ETL processes using Python, Pyspark.

➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.

➢ ETL process monitoring using CloudWatch events.

➢ You will be working in collaboration with other teams. Good communication must.

➢ Must have experience in using AWS services API, AWS CLI and SDK

Professional Attributes:

➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.

➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.

➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.

Qualification:

➢ Degree in Computer Science, Computer Engineering or equivalent.

Salary: Commensurate with experience and demonstrated competence

Skills and requirements

• Experience analyzing complex and varied data in a commercial or academic setting.
• Desire to solve new and complex problems every day.
• Excellent ability to communicate scientific results to both technical and non-technical team members.

Desirable

• A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
• Hands on experience on Python, Pyspark, SQL
• Hands on experience on building End to End Data Pipelines.
• Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
• Hands on Experience in building data pipelines.
• Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
• Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
• Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
• BS degree in math, statistics, computer science or equivalent technical field.
• Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
• Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
• Willing to learn and work on Data Science, ML, AI.

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

• Research and test novel machine learning approaches for analysing large-scale distributed computing applications.
• Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy,  efficacy, and robustness
• Work closely with other functional teams to integrate implemented systems into the SaaS platform
• Suggest innovative and creative concepts and ideas that would improve the overall platform

‍

The ideal candidate must have the following qualifications:

• 5 + years experience in practical implementation and deployment of large customer-facing ML based systems.
• MS or M Tech (preferred) in applied mathematics/statistics;  CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills
• In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python is a must
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Most importantly, you should be someone who is passionate about building new and innovative products that solve tough real-world problems.

Chennai, India