AI / ML Engineer- Data Science | Remote W2 Role

Magnum Technologies, Inc.; United States; Remoto; USD 140.000 - 200.000; Tempo pieno

Descrizione del lavoro

Magnum Technologies, Inc. seeks a senior ML/AI specialist to advance ML foundations, NLP, transformers, and LLM-driven systems across products.

You will work with PyTorch/TensorFlow, RAG, vector databases, and knowledge graphs, delivering scalable AI solutions in cloud environments.

Responsibilities include building ML governance, security, and deployment pipelines with Kubernetes, Docker, and CI/CD, collaborating cross-functionally.

Competenze

• ML/AI fundamentals, evaluation methodologies, and model selection.
• Deep learning frameworks experience (PyTorch/TensorFlow).
• NLP, transformers, LLMs, and generative AI knowledge.
• Hands-on with RAG, vector databases, knowledge graphs, and AI agents.
• Proficiency in Python and Java; proficiency with APIs, microservices, and distributed systems.
• Strong cloud experience with Azure OpenAI, AWS SageMaker, or Vertex AI.
• Experience with Databricks, Snowflake, Spark, Kafka in data engineering.
• Kubernetes, Docker, CI/CD (GitHub Actions/Azure DevOps), Terraform, cloud-native arch.

Conoscenze

ML fundamentals

NLP

Transformers

Deep Learning

LLMs

Agentic AI

Python

Java

APIs

Distributed systems

Strumenti

PyTorch

TensorFlow

RAG

Vector databases

Knowledge graphs

AI agents

Azure OpenAI

Azure AI Services

AWS SageMaker

Google Vertex AI

Databricks

Snowflake

Spark

Kafka

Kubernetes

Docker

GitHub Actions

Azure DevOps

Terraform

Descrizione del lavoro

Required Skills

Machine Learning & AI foundations

Strong grounding in ML fundamentals supervised/unsupervised learning, evaluation methodology, and model selection.

Practical experience with deep learning frameworks (PyTorch and/or TensorFlow).

Solid understanding of NLP and transformer architectures.

Technical Expertise

Strong expertise in Machine Learning, Deep Learning, NLP, Large Language Models (LLMs), and Generative AI.

Hands-on experience with RAG, Vector Databases, Knowledge Graphs, AI Agents, and Agentic AI frameworks.

Proficiency in Python, Java, APIs, Microservices, and distributed system architecture.

Strong knowledge of Azure AI Services, Azure OpenAI, AWS SageMaker, or Google Vertex AI.

Experience with Databricks, Snowflake, Spark, Kafka, and modern data engineering platforms.

Expertise in Kubernetes, Docker, GitHub Actions/Azure DevOps, Terraform, and cloud-native architectures.

Knowledge of Responsible AI, AI Governance, Model Risk Management, and AI Security principles.