Reads like a ML Engineer role: putting models into production.
Chennai, Tamil Nadu, India
Actively hiring, first seen by us 2 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
Build and tune deep learning models using TensorFlow or PyTorch
Develop NLP models for classification, entity recognition, and semantic search
Deploy models with application teams and build CI/CD pipelines for them
Work with business teams to understand context and apply suitable deep learning solutions
Integrate AI/ML models with other applications using REST APIs
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
Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
Integrating AI&ML models with other applications using REST APIs and other connector technologies
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 2
Early. Similar jobs usually come down between day 6 and day 70.
At Cognizant, jobs usually come down by about day 21.
From 4,444 similar postings that came down, and 386 of Cognizant’s. Coming down is not always a hire.
139 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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Yes. We’ve followed 3 other Data Scientist jobs there since August 2026. All 3 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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 Science
Location: Pan India
Experience: 6 to 15 Years
Notice Period: Immediate to 90 days
Mode of Interview: In Person
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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Chennai, Tamil Nadu, India
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