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Senior AI Engineer

Techneplus
Noida, Uttar Pradesh

Apply Now

Job details

Full-time

Qualifications

TensorFlow
CI/CD
Elasticsearch
Azure
Kubernetes
Big data
DevOps
Spark
Git
Google Cloud Platform
Java
Microservices
AWS
C++
Docker
C
Machine learning
Terraform
Continuous integration
Deep learning
Redis
Natural language processing
GitHub
APIs
Kafka
AI
Communication skills
Python
Software architecture

Full job description

Job Information

Date Opened 01/14/2026
Job Type Full time
Industry IT Services
Work Experience 8-10 years
City Noida
State/Province Uttar Pradesh
Country India
Zip/Postal Code 201309

Job Description

Profile: Senior AI Engineer
Exp: 6+ years
Location: Pune/Bangalore/Noida

Budget - 45 Lacs

Job Summary:

Experience

4+ years of experience designing, developing, and deploying ML models in production environments
1+ year of experience in areas such as recommendation systems, pattern recognition, NLP, or time series modeling
Experience with production-grade Python (preferred), as well as Java or C/C++
Hands-on experience with large-scale software architecture, APIs, and model versioning systems

Skills

Expertise in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn
Proficient in cloud-based ML platforms (e.g., Azure ML, Google Cloud Platform, AWS SageMaker)
Solid understanding of machine learning algorithms (e.g., classification, regression, SVMs, ARIMA, ensemble methods, deep learning, neural network)
Strong foundation in probability theory and statistical modeling (generative and discriminative)
Familiarity with DevOps/MLOps practices, CI/CD pipelines, GitHub Actions, Terraform Docker, and Kubernetes
Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
Strong collaboration skills with cross-functional teams (engineering, analytics, product)
Ability to independently manage tasks and thrive in a remote-first or hybrid environment

Preferred Skills

Experience in regulated industries (e.g., finance, healthcare, insurance)
Excellent communication and stakeholder engagement skills
Strong understanding of deep learning architectures (e.g. CNNs, RNNs, Transformers, GANs)
Strong in GPU based accelerating computing technologies (CUDA, Rapids, NeMo, NIM, etc.)
Proficiency in model evaluation, distributed training, and hyperparameter optimization
Proficient in Big Data Theory based large scale data streaming and in-memory database technologies (Spark, Kafka, Redis, Elastic Search)
Strong in automated workflow technologies (GitHub Actions, Terraform, Helmet) and containerization technologies (Docker, Kubernetes)
Proficient in API and Microservices technologies
Track records in large-scale, real-time AI/GenAI/ML database and solution technologies
Background in responsible AI/ML, model interpretability, and fairness auditing.

Apply Now

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