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Eaton Technologies
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Specialist - AI/ML/Gen AI Engineer

Specialist - AI/ML/Gen AI Engineer

Eaton Technologies

10 - 12 years

20 - 25 Lacs

Pune

Posted:2 days ago| Platform:

Apply

Skills Required

Computer science Automation Front end Version control GIT Artificial Intelligence Machine learning Data structures SQL Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Summary

We are seeking a highly experienced AI/ML Engineer with 10 12 years of hands-on experience to lead the complete AI/ML pipeline from data ingestion and exploration to model deployment and monitoring. The ideal candidate will design and implement machine learning models, leveraging advanced Generative AI (GenAI) techniques to drive content generation, summarization, text classification, and intelligent automation. This role requires expertise in large language models (LLMs), including fine-tuning, optimization, and deployment of models such as GPT, BERT, and LLaMA using transfer learning and LoRA techniques. The candidate will also develop Retrieval-Augmented Generation (RAG) pipelines, integrate GenAI APIs and services into internal platforms, and implement guardrails for responsible AI practices. Beyond model development, the AI/ML Engineer will collaborate with product and engineering teams to deliver GenAI-powered features, drive model governance, and mentor junior team members to foster AI innovation. Experience with MLOps, CI/CD, feature engineering, dimensional modeling, and data engineering will be essential for success in this role. This position is perfect for someone passionate about cutting-edge AI/ML advancements, Generative AI applications, and building impactful machine learning solutions for real-world business challenges.

Job Responsibility

Lead the complete
AIML pipeline
from data ingestion and exploration to model deployment and monitoring.
Leads development, build, and test scenrios for data solutions to deliver business value while meeting quality & technical requirements
Accountable for end-to-end delivery of source data acquisition, complex transformation and orchestration pipelines, AI/ML engineering, and front-end visualization
Design, build, and
deploy machine learning models
(classification, regression, deep learning etc) with real-world business applications.
Leverage advanced
GenAI techniques
to solve problems in content generation, summarization, text classification, and intelligent automation.
Fine-tune, optimize, and deploy
LLMs
(e.g., GPT, BERT, LLaMA) for custom use cases using techniques like transfer learning and LoRA.
Develop
prompt engineering frameworks
and reusable GenAI patterns to accelerate model development.
Build
Retrieval-Augmented Generation (RAG)
pipelines for domain-specific applications using vector databases and embedding models.
Integrate
GenAI APIs and services
(e.g., OpenAI, Azure OpenAI, Hugging Face, LangChain) into internal platforms and products.
Implement
guardrails, safety filters
, and evaluation metrics for GenAI models to ensure responsible AI practices.
Perform advanced
text mining
,
semantic search
,
document clustering
, and
knowledge graph generation
using GenAI.
Drive
GenAI model governance
including versioning, bias/fairness assessments, and monitoring drift in deployed systems.
Collaborate with product and engineering teams to deliver GenAI-powered features in production systems.
Mentor junior AI/ML team members and foster adoption of GenAI techniques across the organization.
Design and implement
robust ML models
(classification, regression, deep learning) to solve real-world problems.
Apply
advanced statistical techniques
to derive insights and build predictive models.
Optimize
model performance through hyperparameter
tuning and evaluation metrics analysis.
Deploy models to production environments
using best practices in MLOps and CI/CD pipelines.
Work on state-of-the-art architectures including Transformers, LSTM, CNNs for deep learning use cases (e.g., NLP, computer vision).
Translate complex technical concepts into clear business insights and recommendations.
Lead
end-to-end ML lifecycle
: data exploration, feature engineering, model selection, training, evaluation, deployment, and monitoring.
Develop and fine-tune GenAI models
including foundational models and
LLMs
(fine-tuning, prompt engineering, RAG).
Mentor junior data scientists and ML engineers on best practices, tools, and techniques.

Qualifications:

Bachelore /Master s / PhD in Computer Science, Data Science, Statistics, Mathematics, or related field.

Skills:

10 12 years of experience in applied machine learning and artificial intelligence.
Strong grounding in
statistics
,
probability
, and
mathematics
.
Proven experience in
feature engineering
,
model tuning
, and understanding of
data structures and algorithms
.
Deep knowledge of
classification/regression techniques
,
ensemble methods
, and
deep learning architectures
.
Expertise with
transformer models
(e.g., BERT, GPT),
RNNs
,
CNNs
, etc.
Solid experience with
GenAI
tools and frameworks (e.g., OpenAI, LangChain, HuggingFace Transformers).
Proficiency in programming languages such as
Python
, with experience using ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
Strong knowledge of
model deployment techniques
using Docker, Kubernetes, MLflow, or similar tools.
Experience working with
large-scale datasets
and distributed computing frameworks like
Spark
is a plus.
Good understanding of
data engineering
practices,
ETL pipelines
, and
dimensional modeling
.
Working knowledge of
SQL
,
Snowflake
, and other cloud data warehouses is an added advantage.
Familiarity with
MLOps
principles, version control (Git), and model monitoring tools.
Experience with
cloud platforms
(e.g., Azure, AWS, GCP) for scalable AI/ML deployment.
Experience with
CI/CD pipelines
in ML model delivery.
Excellent communication and stakeholder management skills.

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Eaton Technologies

Appliances, Electrical, and Electronics Manufacturing

Dublin Ireland

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Personal Settings

Specialist - AI/ML/Gen AI Engineer

Experience & Salary

Skills Required

Work Mode

Job Type

Job Description

AIML pipeline

deploy machine learning models

GenAI techniques

LLMs

prompt engineering frameworks

Retrieval-Augmented Generation (RAG)

GenAI APIs and services

guardrails, safety filters

text mining

semantic search

document clustering

knowledge graph generation

GenAI model governance

robust ML models

advanced statistical techniques

model performance through hyperparameter

Deploy models to production environments

end-to-end ML lifecycle

Develop and fine-tune GenAI models

LLMs

statistics

probability

mathematics

feature engineering

model tuning

data structures and algorithms

classification/regression techniques

ensemble methods

deep learning architectures

transformer models

RNNs

CNNs

GenAI

Python

model deployment techniques

large-scale datasets

Spark

data engineering

ETL pipelines

dimensional modeling

SQL

Snowflake

MLOps

cloud platforms

CI/CD pipelines

More Jobs at Eaton Technologies