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AI/ML Engineer

Hybrid in Austin, TX, US • Posted 2 hours ago • Updated 2 hours ago

Contract W2

12 Months

No Travel Required

Hybrid

Depends on Experience

Fitment

Dice Job Match Score™

⭐ Evaluating experience...

Job Details

Skills

Agile
Amazon SageMaker
Amazon Web Services
Apache Kafka
Apache Spark
Artificial Intelligence
Cloud Computing
Collaboration
Continuous Delivery
Continuous Integration
Database
Databricks
Deep Learning
Docker
Flask
Generative Artificial Intelligence (AI)
Good Clinical Practice
Google Cloud Platform
Keras
Kubernetes
Microsoft Azure
Natural Language Processing
Machine Learning (ML)
Training
PyTorch
Scrum
SQL
Machine Learning Operations (ML Ops)
Mentorship
Vector Databases
Predictive Analytics
Python
Technical Drafting
NoSQL

Summary

Senior AI/ML Engineer (12+ Years Experience)

Required Skills:

12+ years of IT experience with 6+ years in AI/ML Engineering.
Strong expertise in Machine Learning, Deep Learning, NLP, Generative AI, LLMs, RAG, and Predictive Analytics.
Hands-on experience with Python, TensorFlow, PyTorch, Scikit-learn, Keras, and XGBoost.
Experience with Vector Databases (Pinecone, Weaviate, Chroma, FAISS).
Knowledge of MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML, Vertex AI).
Experience with Spark, Databricks, Docker, Kubernetes, REST APIs (FastAPI/Flask).
Strong cloud experience in AWS, Azure, or Google Cloud Platform.
Expertise in CI/CD, SQL/NoSQL databases, and scalable AI architectures.
Experience working in Agile/Scrum environments.

Responsibilities:

Design, develop, and deploy enterprise-scale AI/ML and Generative AI solutions.
Build and optimize LLM, RAG, NLP, recommendation, and predictive analytics applications.
Develop MLOps pipelines for model training, deployment, monitoring, and governance.
Lead AI architecture, code reviews, and technical design discussions.
Collaborate with cross-functional teams to deliver AI-driven business solutions.
Mentor junior engineers and drive AI best practices.

Preferred:

Multi-Agent AI Systems, Graph RAG, Knowledge Graphs, Kafka, Reinforcement Learning.
AI Governance, Responsible AI, and Model Explainability.
AWS/Azure/Google Cloud Platform AI/ML Certifications.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10477291
Position Id: 9002279
Posted 2 hours ago

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