Data Scientist 3
Bengaluru, KA, IN
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s listing: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign, develop, and deploy end-to-end AI/ML and Generative AI solutions
Build scalable ML architectures and evaluate modern tools and platforms
Develop production-ready models and deliver them on cloud environments
Establish monitoring, governance, and fail-safe mechanisms for models
Deliver rapid POCs and extract insights from complex datasets
From the employer’s posting
Design, develop, and deploy end-to-end AI/ML and Generative AI solutions that support critical business needs.
Build scalable machine learning architectures and evaluate modern tools, frameworks, and platforms
Develop production-ready models and deliver solutions on cloud environments (preferably Azure)
Establish monitoring, governance, and fail-safe mechanisms to ensure model reliability and continuous improvement.
Deliver rapid POCs and extract meaningful insights from diverse and complex datasets.
Education & alternatives
## Who we’re looking for * 5+ years of experience delivering enterprise-scale data science and AI/ML solutions. * Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or a related field. * Strong programming skills in Python or R and expertise with ML/DL frameworks, including hands-on experience with PyTorch and modern deep learning techniques. * Experience applying machine learning techniques to scientific computing, engineering simulations, surrogate modeling, or related data-intensive problem domains. * Experience with cloud platforms (Azure, AWS, or GCP) and big-data technologies (e.g., Hadoop, Spark). * Proven understanding of MLOps, model deployment, and ML fail-safe principles. * Hands-on experience in leading projects using agile methodologies. * Strong communication and stakeholder-management skills. ## Preferred qualifications
Tools in this posting
- Python
- R
- AWS
- Azure
- Google Cloud (GCP)
- Hadoop
- Spark
- PyTorch
Source — Tool mentions in context
## Who we’re looking for * 5+ years of experience delivering enterprise-scale data science and AI/ML solutions. * Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or a related field. * Strong programming skills in Python or R and expertise with ML/DL frameworks, including hands-on experience with PyTorch and modern deep learning techniques. * Experience applying machine learning techniques to scientific computing, engineering simulations, surrogate modeling, or related data-intensive problem domains. * Experience with cloud platforms (Azure, AWS, or GCP) and big-data technologies (e.g., Hadoop, Spark). * Proven understanding of MLOps, model deployment, and ML fail-safe principles. * Hands-on experience in leading projects using agile methodologies. * Strong communication and stakeholder-management skills. ## Preferred qualifications
## What you’ll do * Design, develop, and deploy end-to-end AI/ML and Generative AI solutions that support critical business needs. * Build scalable machine learning architectures and evaluate modern tools, frameworks, and platforms to strengthen our data science ecosystem, including solutions for Scientific Machine Learning (SciML), surrogate modeling, digital twins, and simulation-driven AI applications. * Develop production-ready models and deliver solutions on cloud environments (preferably Azure) using strong MLOps practices, with exposure to deep learning frameworks such as PyTorch and emerging architectures including physics-informed AI models and neural operators. * Partner closely with data scientists, engineers, and business stakeholders to translate business problems into technical solutions with measurable impact. * Lead technical design discussions, guide teams through complex AI/ML challenges, and foster a collaborative innovation culture. * Establish monitoring, governance, and fail-safe mechanisms to ensure model reliability and continuous improvement. * Deliver rapid POCs and extract meaningful insights from diverse and complex datasets. * Work Schedule: Standard business hours with flexibility to collaborate across teams. ## Who we’re looking for
## Preferred qualifications * Experience designing large-scale AI/ML or GenAI architectures. * Background in building highly scalable production ML systems. * Familiarity with advanced statistical modeling, applied machine learning techniques, and emerging areas such as Scientific Machine Learning (SciML), Physics-Informed AI, Neural Operators, and Digital Twin technologies. * Exposure to frameworks and methodologies such as PINNs, PINO, DeepONet, Fourier Neural Operators (FNO), MeshGraphNets, NVIDIA Modulus, PhysicsNeMo, PyTorch Geometric, PDE learning, operator learning, geometry-aware sampling, or multi-physics simulation is a strong plus. * Experience guiding teams in high-impact technical environments. * Understanding of engineering simulation workflows, scientific computing, or physical systems modeling is desirable. ## Our commitment
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 2, 2026 · 16 days ago
- Recorded sightings
- 108
- Last seen by us
- Oct 18, 2026
- Employer says posted
- Sep 28, 2026
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Bengaluru, KA, IN
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