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Cozzera
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Artificial Intelligence Engineer

Artificial Intelligence Engineer

Cozzera

6 years

0 Lacs

India

Posted:1 month ago| Platform:

Apply

Skills Required

ai ml learning software engineering collaborative design data preprocessing model training evaluation spark docker kubernetes aws gcp latency research algorithms programming numpy tensorflow pytorch fastapi flask azure mlflow airflow statistics hive hadoop github

Work Mode

Remote

Job Type

Full Time

Job Description

Job Title: AI/ML Engineer

Experience: 6+ Years

Location: Remote

Employment Type: Full-Time

Job Summary:

AI/ML Engineer

Key Responsibilities:

Design, develop, and deploy machine learning models for real-world business use cases.
Build end-to-end ML pipelines including data preprocessing, model training, evaluation, and deployment.
Work with large-scale datasets using distributed computing tools like Spark or Dask.
Deploy models in production using tools like Docker, Kubernetes, and cloud services (AWS/GCP/Azure).
Collaborate with data scientists, data engineers, product managers, and software engineers.
Optimize model performance, reduce latency, and ensure robustness in real-time environments.
Research and experiment with new algorithms and ML approaches to improve existing solutions.

Mandatory Skills:

Programming Languages:
Proficiency in
Python
(NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch), and working knowledge of
SQL
.
ML/AI Skills:
Strong understanding of supervised/unsupervised learning, deep learning (CNNs, RNNs, Transformers), NLP, and classical ML algorithms.
Model Deployment:
Experience with
model serving frameworks
(FastAPI, Flask, TensorFlow Serving, TorchServe) and
MLOps
practices.
Cloud Platforms:
Hands-on experience with at least one major cloud provider (
AWS, Azure, or GCP
) for AI/ML workloads.
Tools & Frameworks:
Familiarity with MLFlow, Airflow, DVC, Docker, Kubernetes.
Data Handling:
Experience with handling large datasets, data cleaning, feature engineering, and working with structured/unstructured data.

Preferred Qualifications:

Experience with
Vector Databases
,
LLMs
,
LangChain
, or
Generative AI
solutions.
Knowledge of
CI/CD
in ML workflows and
Infrastructure as Code
(e.g., Terraform).
Background in
statistics, optimization
, and
experiment design
.
Exposure to
Big Data tools
like Spark, Hive, or Hadoop is a plus.
Published papers, GitHub contributions, or Kaggle competition experience is an advantage.

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