Precision Technologies
Machine Learning With AI Engineer
Experience: 5+ Years What We’re Looking For
Minimum 5+ years of hands-on experience in
Artificial Intelligence (AI)
and
Machine Learning (ML)
application development, with strong expertise in Python and ML frameworks. Proficiency in building, training, and deploying
ML models
using frameworks such as
TensorFlow, PyTorch, Scikit-learn, Keras , and
Hugging Face Transformers . Strong working knowledge of
NLP, Computer Vision, Recommendation Systems, and Generative AI models (LLMs, GPT, BERT, etc.) . Experience in developing and deploying
RESTful APIs and microservices
for model integration using
FastAPI, Flask, or Django . Expertise in working with
large datasets , data preprocessing, feature engineering, and performance optimization for ML pipelines. Proficiency with
SQL and NoSQL databases
(PostgreSQL, MySQL, MongoDB) for data storage and retrieval, along with
Big Data platforms
such as Spark or Hadoop. Familiarity with
cloud platforms
such as
AWS (SageMaker, EC2, S3, Lambda), Azure ML , or
GCP AI Platform
for end-to-end ML lifecycle management. Proficiency in
version control systems
like Git and experience with
CI/CD pipelines
for ML model deployment using tools such as
Jenkins, GitHub Actions, or MLflow . Solid understanding of
ML system design, OOP, SOLID principles, and design patterns
for building scalable and maintainable AI-driven applications. Experience with
unit testing and model validation techniques , A/B testing, cross-validation, and monitoring ML models in production. Good understanding of
data pipelines, ETL processes, orchestration tools (Airflow, Luigi, Prefect) , and workflow automation. Strong debugging and performance optimization skills for
training deep learning models
and ensuring efficient inference in production. Experience working in
Agile/Scrum development teams , participating in sprint planning, code reviews, backlog grooming, and collaborative development.
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Experience: 5+ Years What We’re Looking For
Minimum 5+ years of hands-on experience in
Artificial Intelligence (AI)
and
Machine Learning (ML)
application development, with strong expertise in Python and ML frameworks. Proficiency in building, training, and deploying
ML models
using frameworks such as
TensorFlow, PyTorch, Scikit-learn, Keras , and
Hugging Face Transformers . Strong working knowledge of
NLP, Computer Vision, Recommendation Systems, and Generative AI models (LLMs, GPT, BERT, etc.) . Experience in developing and deploying
RESTful APIs and microservices
for model integration using
FastAPI, Flask, or Django . Expertise in working with
large datasets , data preprocessing, feature engineering, and performance optimization for ML pipelines. Proficiency with
SQL and NoSQL databases
(PostgreSQL, MySQL, MongoDB) for data storage and retrieval, along with
Big Data platforms
such as Spark or Hadoop. Familiarity with
cloud platforms
such as
AWS (SageMaker, EC2, S3, Lambda), Azure ML , or
GCP AI Platform
for end-to-end ML lifecycle management. Proficiency in
version control systems
like Git and experience with
CI/CD pipelines
for ML model deployment using tools such as
Jenkins, GitHub Actions, or MLflow . Solid understanding of
ML system design, OOP, SOLID principles, and design patterns
for building scalable and maintainable AI-driven applications. Experience with
unit testing and model validation techniques , A/B testing, cross-validation, and monitoring ML models in production. Good understanding of
data pipelines, ETL processes, orchestration tools (Airflow, Luigi, Prefect) , and workflow automation. Strong debugging and performance optimization skills for
training deep learning models
and ensuring efficient inference in production. Experience working in
Agile/Scrum development teams , participating in sprint planning, code reviews, backlog grooming, and collaborative development.
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