Purple Drive
ob Summary:
We are seeking a highly skilled
AI Applied Engineer
to design, develop, and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable, production-ready applications that deliver real-world business impact.
Key Responsibilities:
Design, develop, and deploy
AI and Machine Learning (ML)
solutions for digital transformation initiatives. Collaborate with data scientists to
operationalize AI models
using MLOps best practices. Integrate
AI-driven components
into existing enterprise systems and cloud platforms. Build scalable
data pipelines
to support model training, testing, and deployment. Leverage frameworks such as
TensorFlow, PyTorch, or Scikit-learn
for model development and optimization. Work with
cloud-based AI services
(Azure AI, AWS SageMaker, Google Vertex AI, etc.) for large-scale deployments. Apply
Natural Language Processing (NLP) ,
Computer Vision , and
Predictive Analytics
techniques to solve complex business challenges. Partner with cross-functional teams to identify opportunities for
AI automation and digital innovation . Ensure solutions meet performance, scalability, and ethical AI standards. Maintain detailed
technical documentation , conduct code reviews, and mentor junior engineers. Required Skills & Qualifications:
Strong programming skills in
Python ,
Java , or
C# . Hands-on experience with
AI/ML frameworks
(TensorFlow, PyTorch, Keras, Scikit-learn). Experience deploying AI models into
production environments . Knowledge of
MLOps tools
(MLflow, Kubeflow, Airflow, Docker, Kubernetes). Familiarity with
data engineering
tools and ETL pipelines. Understanding of
cloud platforms
(Azure, AWS, or GCP) and their AI/ML services. Proven experience in
digital transformation
or
intelligent automation
projects. Strong analytical and problem-solving abilities with a focus on innovation. Excellent collaboration and communication skills. Nice to Have:
Experience in
Generative AI (LLMs, Prompt Engineering, LangChain, RAG frameworks) . Exposure to
Edge AI ,
IoT , or
Real-time analytics . Familiarity with
API integration
and
microservices architecture . Knowledge of
Responsible AI
principles and model governance. Education:
Bachelor's or Master's degree in
Computer Science ,
Artificial Intelligence ,
Data Science , or a related technical field.
We are seeking a highly skilled
AI Applied Engineer
to design, develop, and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable, production-ready applications that deliver real-world business impact.
Key Responsibilities:
Design, develop, and deploy
AI and Machine Learning (ML)
solutions for digital transformation initiatives. Collaborate with data scientists to
operationalize AI models
using MLOps best practices. Integrate
AI-driven components
into existing enterprise systems and cloud platforms. Build scalable
data pipelines
to support model training, testing, and deployment. Leverage frameworks such as
TensorFlow, PyTorch, or Scikit-learn
for model development and optimization. Work with
cloud-based AI services
(Azure AI, AWS SageMaker, Google Vertex AI, etc.) for large-scale deployments. Apply
Natural Language Processing (NLP) ,
Computer Vision , and
Predictive Analytics
techniques to solve complex business challenges. Partner with cross-functional teams to identify opportunities for
AI automation and digital innovation . Ensure solutions meet performance, scalability, and ethical AI standards. Maintain detailed
technical documentation , conduct code reviews, and mentor junior engineers. Required Skills & Qualifications:
Strong programming skills in
Python ,
Java , or
C# . Hands-on experience with
AI/ML frameworks
(TensorFlow, PyTorch, Keras, Scikit-learn). Experience deploying AI models into
production environments . Knowledge of
MLOps tools
(MLflow, Kubeflow, Airflow, Docker, Kubernetes). Familiarity with
data engineering
tools and ETL pipelines. Understanding of
cloud platforms
(Azure, AWS, or GCP) and their AI/ML services. Proven experience in
digital transformation
or
intelligent automation
projects. Strong analytical and problem-solving abilities with a focus on innovation. Excellent collaboration and communication skills. Nice to Have:
Experience in
Generative AI (LLMs, Prompt Engineering, LangChain, RAG frameworks) . Exposure to
Edge AI ,
IoT , or
Real-time analytics . Familiarity with
API integration
and
microservices architecture . Knowledge of
Responsible AI
principles and model governance. Education:
Bachelor's or Master's degree in
Computer Science ,
Artificial Intelligence ,
Data Science , or a related technical field.