We are looking for a Data Scientist with strong AI/ML engineering skills to join our high-impact team at KrtrimaIQ Cognitive Solutions. This is not a notebook-only role — you must have production-grade experience deploying and scaling AI/ML models in cloud environments, especially GCP, AWS, or Azure.

This role involves building, training, deploying, and maintaining ML models at scale, integrating them with business applications. Basic model prototyping won't qualify — we’re seeking hands-on expertise in building scalable machine learning pipelines.

Key Responsibilities

Design, train, test, and deploy end-to-end ML models on GCP (or AWS/Azure) to support product innovation and intelligent automation.

Implement GenAI use cases using LLMs

Perform complex data mining and apply statistical algorithms and ML techniques to derive actionable insights from large datasets.

Drive the development of scalable frameworks for automated insight generation, predictive modeling, and recommendation systems.

Work on impactful AI/ML use cases in Search & Personalization, SEO Optimization, Marketing Analytics, Supply Chain Forecasting, and Customer Experience.

Implement real-time model deployment and monitoring using tools like Kubeflow, Vertex AI, Airflow, PySpark, etc.

Collaborate with business and engineering teams to frame problems, identify data sources, build pipelines, and ensure production-readiness.

Maintain deep expertise in cloud ML architecture, model scalability, and performance tuning.

Stay up to date with AI trends, LLM integration, and modern practices in machine learning and deep learning.

Technical Skills Required Core ML & AI Skills (Must-Have):

Strong hands-on ML engineering (70% of the role) — supervised/unsupervised learning, clustering, regression, optimization.

Experience with real-world model deployment and scaling, not just notebooks or prototypes.

Good understanding of ML Ops, model lifecycle, and pipeline orchestration.

Strong with Python 3, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Seaborn, Matplotlib, etc.

SQL proficiency and experience querying large datasets.

Deep understanding of linear algebra, probability/statistics, Big-O, and scientific experimentation.

Cloud experience in GCP (preferred), AWS, or Azure.

Cloud & Big Data Stack

Hands-on experience with:

GCP tools – Vertex AI, Kubeflow, BigQuery, GCS

Or equivalent AWS/Azure ML stacks

Familiar with Airflow, PySpark, or other pipeline orchestration tools.

Experience reading/writing data from/to cloud services.

Qualifications

Bachelor's/Master’s/Ph.D. in Computer Science, Mathematics, Engineering, Data Science, Statistics, or related quantitative field.

4+ years of experience in data analytics and machine learning roles.

2+ years of experience in Python or similar programming languages (Java, Scala, Rust).

Must have experience deploying and scaling ML models in production.

Nice to Have

Experience with LLM fine-tuning, Graph Algorithms, or custom deep learning architectures.

Background in academic research to production applications.

Building APIs and monitoring production ML models.

Familiarity with advanced math – Graph Theory, PDEs, Optimization Theory.

Communication & Collaboration

Strong ability to explain complex models and insights to both technical and non-technical stakeholders.

Ask the right questions, clarify objectives, and align analytics with business goals.

Comfortable working cross-functionally in agile and collaborative teams.

Important Note:

This is a Data Science-heavy role — 70% of responsibilities involve building, training, deploying, and scaling AI/ML models.

Cloud experience is mandatory (GCP preferred, AWS/Azure acceptable).

Only candidates with hands-on experience in deploying ML models into production (not just notebooks) will be considered.

Job description

Key Responsibilities

Design, train, test, and deploy end-to-end ML models on GCP (or AWS/Azure) to support product innovation and intelligent automation.

Implement GenAI use cases using LLMs

Perform complex data mining and apply statistical algorithms and ML techniques to derive actionable insights from large datasets.

Drive the development of scalable frameworks for automated insight generation, predictive modeling, and recommendation systems.

Work on impactful AI/ML use cases in Search & Personalization, SEO Optimization, Marketing Analytics, Supply Chain Forecasting, and Customer Experience.

Implement real-time model deployment and monitoring using tools like Kubeflow, Vertex AI, Airflow, PySpark, etc.

Collaborate with business and engineering teams to frame problems, identify data sources, build pipelines, and ensure production-readiness.

Maintain deep expertise in cloud ML architecture, model scalability, and performance tuning.

Stay up to date with AI trends, LLM integration, and modern practices in machine learning and deep learning.

Technical Skills Required Core ML & AI Skills (Must-Have):

Strong hands-on ML engineering (70% of the role) — supervised/unsupervised learning, clustering, regression, optimization.

Experience with real-world model deployment and scaling, not just notebooks or prototypes.

Good understanding of ML Ops, model lifecycle, and pipeline orchestration.

Strong with Python 3, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Seaborn, Matplotlib, etc.

SQL proficiency and experience querying large datasets.

Deep understanding of linear algebra, probability/statistics, Big-O, and scientific experimentation.

Cloud experience in GCP (preferred), AWS, or Azure.

Cloud & Big Data Stack

Hands-on experience with:

GCP tools – Vertex AI, Kubeflow, BigQuery, GCS

Or equivalent AWS/Azure ML stacks

Familiar with Airflow, PySpark, or other pipeline orchestration tools.

Experience reading/writing data from/to cloud services.

Qualifications

Bachelor's/Master’s/Ph.D. in Computer Science, Mathematics, Engineering, Data Science, Statistics, or related quantitative field.

4+ years of experience in data analytics and machine learning roles.

2+ years of experience in Python or similar programming languages (Java, Scala, Rust).

Must have experience deploying and scaling ML models in production.

Nice to Have

Experience with LLM fine-tuning, Graph Algorithms, or custom deep learning architectures.

Background in academic research to production applications.

Building APIs and monitoring production ML models.

Familiarity with advanced math – Graph Theory, PDEs, Optimization Theory.

Communication & Collaboration

Strong ability to explain complex models and insights to both technical and non-technical stakeholders.

Ask the right questions, clarify objectives, and align analytics with business goals.

Comfortable working cross-functionally in agile and collaborative teams.

Important Note:

This is a Data Science-heavy role — 70% of responsibilities involve building, training, deploying, and scaling AI/ML models.

Cloud experience is mandatory (GCP preferred, AWS/Azure acceptable).

Only candidates with hands-on experience in deploying ML models into production (not just notebooks) will be considered.

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About krtrimaiq cognitive solutions

Founded :

2019

Type :

Products & Services

Size :

20-100

Stage :

Profitable

About

Founded in 2019 by a data and AI veteran with over 30 years of industry experience, krtrimaIQ was built with one belief: AI shouldn't be a distant promise; it should be working inside your business today.

Trusted by global players as an innovation partner and delivery backbone, our team brings together deep academic grounding, real-world experience, and a shared commitment to building systems that deliver quietly, reliably, and at scale.

Company social profiles

N/A

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Experience in HTML, CSS
Understanding of React will be a bonus

The Candidate should have knowledge and experience with specified technologies:

Great at building server-side code in NodeJs & ExpressJs
Experience with NoSQL databases such as MongoDB
Experience in building and consuming REST API
Authentication and authorisation using JWT tokens
Proficient understanding of code versioning tools, such as Git
DevOps knowledge especially in AWS EC2 and S3
Knowledge of headless Chrome, Puppeteer will be huge plus
Experience in HTML, CSS
Understanding of React will be a bonus

Analyst - Search Engine Optimization

at Vedantu

8 recruiters

Posted by Maqsood Pasha

Bengaluru (Bangalore)

4 - 6 yrs

₹5L - ₹6L / yr

Search Engine Optimization (SEO)

SEO management

HTML/CSS

Google Analytics

Web Analytics

+1 more

- Reviewing and analyzing the sites for areas that can be improved and optimized.- Preparing detailed strategy reports.- Monitoring and creating traffic reports from Google Analytics (Month on month).- Tracking Search Analytics data (Webmaster - Imp, Clicks, Position & CTR).- Identifying powerful keywords to drive the most valuable traffic.- Filling websites and other content with effective keywords.- Assigning effective SEO content for blogs, websites, forums, bookmarking and social media accounts to content writers.- Developing link building strategies which help to rank seed keywords.- Managing Backlinks date from Search console or paid tool (Knowledge about disavow tool for submitting spam links).- Analyzing keywords and SEO techniques used by competitors.

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