Artificial Intelligence Consultant

1 month ago

atlanta, United States Staffing Technologies Full time

The AI/ML Developer will leverage Mathematical Programming and AI/DL Algorithms and Technologies to drive research and development, addressing complex business challenges. This role focuses on utilizing cutting-edge methodologies and technologies to create solutions.


Focuses on designing, developing, and implementing machine learning models and AI applications to solve business problems. Here are some key responsibilities:

  • Designing and Developing Models: Creating machine learning and deep learning models to address specific business needs.
  • Data Analysis: Analyzing large datasets to extract meaningful insights and improve model performance.
  • Algorithm Implementation: Implementing AI/ML algorithms to solve complex problems.
  • Collaboration: Working closely with cross-functional teams to integrate AI solutions into existing systems.
  • Model Testing and Validation: Running experiments to test the effectiveness of models and making necessary adjustments.
  • Automation: Identifying repetitive tasks and developing automated solutions to increase efficiency.


Qualifications:

1. Educational Background:

Preferred Master's or Ph.D. in Science and Engineering disciplines such as Mathematics, Physics, Economics, Computer Science, or related fields with a focus on AI/ML.

2. Business Problem Solving:

Expertise in defining business problems with mathematics including, but not limited to, risk and cost management, price and revenue optimization, sales/operational process mining and simulation, and time series forecasting.

3. AI/ML Technology Proficiency:

Hands-on experience with advanced AI/ML tools and frameworks like Sciki-Learn, TensorFlow, Keras, PyTorch, RAG, Langchain, LlamaIndex, Neo4j, and expertise in NLP, LM, CV techniques.

4. Programming Skills:

Proficient in programming languages and platforms like Python, PySpark, Scala, C++, CUDA, SQL/NoSQL/Vector DB.

5. Algorithm Expertise:

Strong knowledge of AI/ML algorithms including Bayesian Inference, XGBoost, CNNs, RNNs, GNNs, KG, Generative Modeling, RAG.

6. DevOps and Cloud Tools:

Familliar with platforms and tools like Docker, Kubernetes, GitHub Actions, Terraform, GPU (CUDA/Nemo/NIM), Azure (Azure ML, Azure AI, Databricks).

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