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Day 46
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Kolkata, West Bengal, India
Live, first seen by us 46 days agoWork setup in the employer’s posting: hybrid remoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Apply machine learning and deep learning algorithms to business problems
Design, develop and deploy deep learning models using TensorFlow or PyTorch
Build NLP models for classification, entity recognition, summarization and search
Deploy models on cloud or on-prem and build CI/CD pipelines for them
Integrate AI and ML models with other applications using REST APIs
apply Machine Learning & Deep Learning algorithms to solve business challenges
Design , develop & deploy Deep learning models using Tensorflow / Pytorch
Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search
Work with application teams, in deploying models on cloud as a service or on-prem
Integrating AI&ML models with other applications using REST APIs and other connector technologies
Experience : 5+ to 13 Years
Python / R / SQL / Cloud data pipelines
Design , develop & deploy Deep learning models using Tensorflow / Pytorch
Sufficient expertise in machine learning, mathematical and statistical sciences
Use of versioning & Collaborative tools like Git / Github
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Day 46
Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
140 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge 3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch
· Appreciation of digital ethics, data privacy will be important · Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus · Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus
· Keen contributor to open source communities, and communities like Kaggle · Ability to process Huge amount of Data using Pyspark/Hadoop · Development & Application of Reinforcement Learning
6. Optimize and tune Deep Learnings model for best possible accuracy 7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau 8. Work with application teams, in deploying models on cloud as a service or on-prem
3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch 5. Experience in using Deep learning models with text, speech, image and video data
5. Experience in using Deep learning models with text, speech, image and video data a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Role – AIML Data Scientist
Location :Pan India
Experience : 5+ to 13 Years
Notice Period : Immediate to 90 days
Mode of Interview - In Person (Chennai)
Job Description:
1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges
a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem
b. Improve Model accuracy to deliver greater business impact
c. Estimate business impact due to deployment of model
2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines
4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch
5. Experience in using Deep learning models with text, speech, image and video data
a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc
b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
c. Knowledge of State of the art Deep learning algorithms
6. Optimize and tune Deep Learnings model for best possible accuracy
7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau
8. Work with application teams, in deploying models on cloud as a service or on-prem
a. Deployment of models in Test / Control framework for tracking
b. Build CI/CD pipelines for ML model deployment
9. Integrating AI&ML models with other applications using REST APIs and other connector technologies
10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.
· Technology/Subject Matter Expertise
· Sufficient expertise in machine learning, mathematical and statistical sciences
· Use of versioning & Collaborative tools like Git / Github
· Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
· Develop prototype level ideas into a solution that can scale to industrial grade strength
· Ability to quantify & estimate the impact of ML models
· Softskills Profile
· Ability to communicate key messages effectively, and articulate strong opinions in large forums
· Desirable Experience:
· Keen contributor to open source communities, and communities like Kaggle
· Ability to process Huge amount of Data using Pyspark/Hadoop
· Development & Application of Reinforcement Learning
· Knowledge of Optimization/Genetic Algorithms
· Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
· Optimize and tune deep learning model for best possible accuracy
· Understanding of stream data processing, RPA, edge computing, AR/VR etc
· Appreciation of digital ethics, data privacy will be important
· Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
· Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus
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Kolkata, West Bengal, India
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