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Cozzera
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AI/ML Engineer

AI/ML Engineer

Cozzera

4 years

0 Lacs

noida uttar pradesh india

Posted:11 hours ago| Platform:

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Skills Required

ai ml design reliability automate analysis learning automation devops management splunk datadog data analytics correlation model visualization openai azure engineering tensorflow pytorch aws gcp docker itil apache kafka

Work Mode

On-site

Job Type

Full Time

Job Description

Job Title:

Experience:

Location:

Work Hours:

Employment Type:

About the Role:

AI/ML Ops Engineer

machine learning pipelines, anomaly detection, and automation frameworks

Key Responsibilities

AI/ML Development:
Design, build, and deploy ML models for anomaly detection, predictive incident management, and automated root cause analysis.
Tool Integration:
Integrate AIOps capabilities with enterprise observability tools like
Splunk, Datadog, Prometheus, and AppDynamics
.
Collaboration:
Work closely with SRE, DevOps, and IT operations teams to identify automation opportunities and enhance operational resilience.
Data Engineering:
Develop and maintain data pipelines for log, metric, and event ingestion, transformation, and analysis.
NLP for Ops:
Apply NLP techniques to log analytics, intelligent alert correlation, and contextual insights generation.
Model Management:
Monitor, retrain, and optimize ML models for sustained performance in production environments.
Visualization:
Build dashboards and visualization tools to enable real-time operational intelligence and insight delivery.
GenAI Integration:
Implement
GenAI-based automation
and integrate AI SDKs (e.g., OpenAI, Azure AI, LangChain) to enable intelligent workflows.

Required Qualifications & Skills

Bachelor’s or Master’s degree in
Computer Science, Data Science, or a related field
.
3+ years
of hands-on experience in AI/ML engineering — ideally in IT operations, DevOps, or AIOps domains.
Proficiency in
Python
and key ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Strong understanding of
time-series analysis, anomaly detection, and predictive modeling
.
Experience implementing
GenAI
and integrating
AI SDKs
(OpenAI, Azure AI, LangChain, etc.).
Hands-on experience with
cloud platforms
(AWS, Azure, GCP) and
containerized deployments
(Docker, Kubernetes).
Familiarity with
CI/CD pipelines
and
MLOps workflows
.
Understanding of
ITSM / ITIL processes
and related tools.

Nice to Have

Experience with
observability platforms
such as Grafana or Elastic Stack.
Exposure to
data engineering frameworks
like Apache Kafka or Airflow.
Experience developing
self-healing or automated incident resolution systems
.

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