Mechanized AI Inc.
Machine Learning Engineer
Mechanized AI Inc., Little Rock, Arkansas, United States
Job Description:
Machine Learning Engineer Location:
Buenos Aires, Argentina (Remote work options available) Company:
Mechanized AI About Us: Mechanized AI is at the forefront of AI innovation, leveraging advanced technologies to solve complex real-world problems. We are dedicated to creating cutting-edge solutions that drive modernization and efficiency across industries. As a growing team of passionate professionals, we are committed to fostering an environment that encourages creativity, collaboration, and continuous learning. Key Responsibilities: Evaluate ML/DL/LLM models Detect and handle model decay & data drift Experience Requirements: 4+ years
in Machine Learning/Deep Learning/Generative AI (Experience in enterprise companies or startups; teaching or academic experience like Masters/PhD does not count) 1+ year
experience with TensorFlow, PyTorch, or Keras 1+ year
experience in deploying models to production and managing/monitoring them 1+ year
with cloud platforms (AWS/GCP/Azure) 1+ year
in MLOps 1+ year
client-facing experience in AI projects 6+ months
experience with Large Language Models (LLMs) and Generative AI Skills & Expertise: Strong focus on at least one of the following AI specialities:
MLOps Classic ML (tabular, regression) Classic DL (Computer Vision, NLP, tabular, regression) Generative AI Deep Reinforcement Learning (DRL) Full-stack ML
Familiarity with Prompt Engineering: Approaches and best practices Experience with the following tools and techniques is highly desired:
PySpark Agent development Fine-tuning LLMs Retrieval-Augmented Generation (RAG) optimization Vector Databases LLM Architecture & techniques for performance Model quantization Data privacy and security (e.g., adversarial attacks, red teaming, integrity)
#J-18808-Ljbffr
Machine Learning Engineer Location:
Buenos Aires, Argentina (Remote work options available) Company:
Mechanized AI About Us: Mechanized AI is at the forefront of AI innovation, leveraging advanced technologies to solve complex real-world problems. We are dedicated to creating cutting-edge solutions that drive modernization and efficiency across industries. As a growing team of passionate professionals, we are committed to fostering an environment that encourages creativity, collaboration, and continuous learning. Key Responsibilities: Evaluate ML/DL/LLM models Detect and handle model decay & data drift Experience Requirements: 4+ years
in Machine Learning/Deep Learning/Generative AI (Experience in enterprise companies or startups; teaching or academic experience like Masters/PhD does not count) 1+ year
experience with TensorFlow, PyTorch, or Keras 1+ year
experience in deploying models to production and managing/monitoring them 1+ year
with cloud platforms (AWS/GCP/Azure) 1+ year
in MLOps 1+ year
client-facing experience in AI projects 6+ months
experience with Large Language Models (LLMs) and Generative AI Skills & Expertise: Strong focus on at least one of the following AI specialities:
MLOps Classic ML (tabular, regression) Classic DL (Computer Vision, NLP, tabular, regression) Generative AI Deep Reinforcement Learning (DRL) Full-stack ML
Familiarity with Prompt Engineering: Approaches and best practices Experience with the following tools and techniques is highly desired:
PySpark Agent development Fine-tuning LLMs Retrieval-Augmented Generation (RAG) optimization Vector Databases LLM Architecture & techniques for performance Model quantization Data privacy and security (e.g., adversarial attacks, red teaming, integrity)
#J-18808-Ljbffr