10,075 Tensorflow jobs in India

**Job Types**: Full-time, Regular / Permanent, Contractual / Temporary, Freelance
Contract length: 5 days

**Salary**: ₹1,000.00 per hour

**Benefits**:

- Flexible schedule
- Food provided

Schedule:

- Day shift
- Flexible shift
- Monday to Friday
- Morning shift

Supplemental pay types:

- Joining bonus
- Performance bonus
- Shift allowance

Ability to commute/relocate:

- Delhi, Delhi: Reliably commute or planning to relocate before starting work (required)

**Education**:

- Diploma (preferred)

**Experience**:

- training: 1 year (required)
- total work: 5 years (required)

**Language**:

- English (preferred)

**Avant de postuler à un emploi, sélectionnez votre langue de préférence parmi les options disponibles en haut à droite de cette page.**
Découvrez votre prochaine opportunité au sein d'une organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu'il faut faire pour diriger UPS vers l'avenir : des personnes passionnées dotées d'une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l'autonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d'aujourd'hui et de demain.
**Fiche de poste :**
JOB SUMMARY
This position creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects.
RESPONSIBILITIES
- Defines key data sources from UPS and external sources to deliver models.
- Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems.
- For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts
- Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.
- Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives.
- Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling.
- Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders.
- Presents operationalized analytic findings and provides recommendations.
- Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction
- Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions.
QUALIFICATIONS
Requirements:
-Ability to take a data science problem from start to finish, use pytorch/tensorflow to build the full model product.
- Strong analytical skills and attention to detail.
- Able to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.
- Expertise with statistical techniques, machine learning or operations research and their application in business applications.
- Expertise in R, SQL, Python.
- Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production at scale.
- Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows.
- Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms.
- Solid oral and written communication skills, especially around analytical concepts and methods.
- Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience.
- Master's Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.
Preferences:
- Familiarity with Java or C+ **Type de contrat:**
en CDI
_Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés._

**Before you apply to a job, select your language preference from the options available at the top right of this page.**
Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow-people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.
**Job Description:**
JOB SUMMARY
This position creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects.
RESPONSIBILITIES
- Defines key data sources from UPS and external sources to deliver models.
- Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems.
- For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts
- Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.
- Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives.
- Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling.
- Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders.
- Presents operationalized analytic findings and provides recommendations.
- Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction
- Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions.
QUALIFICATIONS
Requirements:
-Ability to take a data science problem from start to finish, use pytorch/tensorflow to build the full model product.
- Strong analytical skills and attention to detail.
- Able to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.
- Expertise with statistical techniques, machine learning or operations research and their application in business applications.
- Expertise in R, SQL, Python.
- Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production at scale.
- Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows.
- Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms.
- Solid oral and written communication skills, especially around analytical concepts and methods.
- Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience.
- Master's Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.
Preferences:
- Familiarity with Java or C+ **Employee Type:**
Permanent
UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Avant de postuler à un emploi, sélectionnez votre langue de préférence parmi les options disponibles en haut à droite de cette page.

Découvrez votre prochaine opportunité au sein d&aposune organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu'il faut faire pour diriger UPS vers l&aposavenir : des personnes passionnées dotées d'une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l&aposautonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d&aposaujourd&aposhui et de demain.

Job Summary

Fiche de poste :

This position creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects.

Responsibilities

• Defines key data sources from UPS and external sources to deliver models.
• Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems.
• For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts
• Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.
• Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives.
• Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling.
• Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders.
• Presents operationalized analytic findings and provides recommendations.
• Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction
• Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions.
  
  

Qualifications

Requirements:

• Ability to take a data science problem from start to finish, use pytorch/tensorflow to build the full model product.
• Strong analytical skills and attention to detail.
• Able to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.
• Expertise with statistical techniques, machine learning or operations research and their application in business applications.
• Expertise in R, SQL, Python.
• Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production at scale.
• Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows.
• Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms.
• Solid oral and written communication skills, especially around analytical concepts and methods.
• Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience.
• Master's Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.
  
  

Preferences

• Familiarity with Java or C++
  
  

Type De Contrat

en CDI

Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés.

Skills Required
Cloud Services, Machine Learning, Statistical Modeling, Tensorflow, Sql, Python, Pytorch

Vayuz Technologies is seeking a highly skilled and experienced Machine Learning Engineer with expertise in Python and TensorFlow to join our innovative team. You will be instrumental in developing, optimizing, and deploying sophisticated ML and Deep Learning models, working with complex datasets, and ensuring the reliability and performance of our AI-driven solutions in production environments.

Key Responsibilities

• Data Analysis & Feature Engineering : Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets.
• Model Development & Optimization : Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
• Deep Learning Implementation : Design and implement advanced Deep Learning models , including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Imbalanced Data Handling : Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
• Model Deployment & Monitoring : Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
• Cross-Functional Collaboration : Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
• Statistical & Mathematical Application : Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
• Innovation & Research : Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Requirements

• Hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing.
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn , and other relevant ML frameworks and libraries.
• Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications

• Experience with Big Data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices .
• Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

Skills Required
Machine Learning, Python Programming, Tensorflow, Data Analysis, Deep Learning, Statistical Analysis

Vayuz Technologies is seeking a highly skilled and experienced Machine Learning Engineer with expertise in Python and TensorFlow to join our innovative team. You will be instrumental in developing, optimizing, and deploying sophisticated ML and Deep Learning models, working with complex datasets, and ensuring the reliability and performance of our AI-driven solutions in production environments.

Key Responsibilities

• Data Analysis & Feature Engineering : Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets.
• Model Development & Optimization : Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
• Deep Learning Implementation : Design and implement advanced Deep Learning models , including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Imbalanced Data Handling : Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
• Model Deployment & Monitoring : Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
• Cross-Functional Collaboration : Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
• Statistical & Mathematical Application : Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
• Innovation & Research : Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Requirements

• Hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing.
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn , and other relevant ML frameworks and libraries.
• Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications

• Experience with Big Data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices .
• Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

Skills Required
Machine Learning, Python Programming, Tensorflow, Data Analysis, Deep Learning, Statistical Analysis

Vayuz Technologies is seeking a highly skilled and experienced Machine Learning Engineer with expertise in Python and TensorFlow to join our innovative team. You will be instrumental in developing, optimizing, and deploying sophisticated ML and Deep Learning models, working with complex datasets, and ensuring the reliability and performance of our AI-driven solutions in production environments.

Key Responsibilities

• Data Analysis & Feature Engineering : Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets.
• Model Development & Optimization : Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
• Deep Learning Implementation : Design and implement advanced Deep Learning models , including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Imbalanced Data Handling : Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
• Model Deployment & Monitoring : Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
• Cross-Functional Collaboration : Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
• Statistical & Mathematical Application : Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
• Innovation & Research : Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Requirements

• Hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing.
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn , and other relevant ML frameworks and libraries.
• Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications

• Experience with Big Data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices .
• Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

Skills Required
Machine Learning, Python Programming, Tensorflow, Data Analysis, Deep Learning, Statistical Analysis

Vayuz Technologies is seeking a highly skilled and experienced Machine Learning Engineer with expertise in Python and TensorFlow to join our innovative team. You will be instrumental in developing, optimizing, and deploying sophisticated ML and Deep Learning models, working with complex datasets, and ensuring the reliability and performance of our AI-driven solutions in production environments.

Key Responsibilities

• Data Analysis & Feature Engineering: Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets.
• Model Development & Optimization: Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
• Deep Learning Implementation: Design and implement advanced Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Imbalanced Data Handling: Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
• Model Deployment & Monitoring: Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
• Cross-Functional Collaboration: Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
• Statistical & Mathematical Application: Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
• Innovation & Research: Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Requirements

• Hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing.
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn, and other relevant ML frameworks and libraries.
• Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications

• Experience with Big Data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices.
• Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

Skills Required
Machine Learning, Python Programming, Tensorflow, Deep Learning, Hadoop, Spark

Vayuz Technologies is seeking a highly skilled and experienced Machine Learning Engineer with expertise in Python and TensorFlow to join our innovative team. You will be instrumental in developing, optimizing, and deploying sophisticated ML and Deep Learning models, working with complex datasets, and ensuring the reliability and performance of our AI-driven solutions in production environments.

Key Responsibilities

• Data Analysis & Feature Engineering : Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets.
• Model Development & Optimization : Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
• Deep Learning Implementation : Design and implement advanced Deep Learning models , including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Imbalanced Data Handling : Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
• Model Deployment & Monitoring : Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
• Cross-Functional Collaboration : Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
• Statistical & Mathematical Application : Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
• Innovation & Research : Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Requirements

• Hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing.
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn , and other relevant ML frameworks and libraries.
• Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications

• Experience with Big Data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices .
• Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

Skills Required
Machine Learning, Python Programming, Tensorflow, Data Analysis, Deep Learning, Statistical Analysis