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Machine Learning Engineer

Machine Learning Engineer

Rmsi

3 - 5 years

0 Lacs

noida

Posted:None| Platform:

Apply

Skills Required

tensorflow cnn rnn ai solutions python algorithm development opencv algorithm design keras

Work Mode

Work from Office

Job Type

Full Time

Job Description

Role & responsibilities

Role Overview:

Software Engineer Machine Learning

Must Have:

3–5 years of hands-on experience
in designing or implementing AI/ML solutions, preferably in enterprise or large-scale environments.
Strong programming skills in Python
, including use of libraries such as TensorFlow, Keras, NumPy, Pandas, scikit-learn, and OpenCV.
Experience with
Convolutional Neural Networks (CNNs)
for real-time object detection using models like
YOLO
, and segmentation using
SAM
and
U-Net
, with practical use of multiple backbones.
Proficiency in
image classification
using CV models like
VGG, YOLOv5
, etc.
Experience with
machine learning algorithms
—both supervised and unsupervised—for classification and regression tasks.
Experience in
Generative AI and Large Language Models (LLMs)
, including
speech-to-text
and
multi-modal input
models.
Strong knowledge of
data structures, algorithms
, and
mathematics/statistics
related to AI.
Experience with
LSTM/Recurrent Neural Networks (RNNs)
or hybrid neural architectures.
Basic understanding of
computer vision concepts and GIS support functions
.

Should Have:

Understanding of
MLOps/LLMOps workflows
for scalable AI deployments.
Experience with
agent-based AI systems (Agentic AI)
or agent design patterns.
Experience working with or contributing to
enterprise-grade data platforms
, ensuring performance and interoperability with AI workloads.
Exposure to
segmentation techniques
for extracting coarse features and creating multiple image segments.
Good communication, collaboration, and analytical skills for engaging with cross-functional teams.

Could Have:

Certifications
in AI/ML or cloud platforms (AWS, Azure, GCP).
Familiarity with
Theano, SciPy
, and other scientific computing libraries.
Experience in AI-focused
research, innovation programs
, or open-source contributions.
Interest in exploring
emerging AI paradigms
such as
federated learning
,
multi-agent systems
, and
Responsible AI
practices.

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