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# AI ML Data Engineer

- **Company:** Propertyvalue Quantum Technologies Llc
- **Location:** Baltimore, MD, United States
- **Salary:** $187,200.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Computer Programming, Extract Transform Load (ETL), Machine Learning, Natural Language Processing, Tensorflow, Systems Integration, Reinforcement Learning, Data Processing, Feature Engineering, Deep Learning, Generative AI, Machine Learning Operations, Unsupervised Learning
- **Published:** September 7, 2026
- **Apply:** https://www.dice.com/job-detail/dbef42ab-44d1-45fc-9e19-1fa58def18cd

## About the Role

1. Proven experience as an ML engineer or similar role
 2. Solid knowledge of ML and deep learning fundamentals with experience in one or more of computer vision, natural language processing, speech, reinforcement learning, generative models, etc.
 3. Knowledge of common ML frameworks and libraries.
 4. Strong programming skills with proven experience implementing ML solutions.
 5. Expertise in data manipulation, exploratory data analysis, and feature engineering.
 6. Excellent problem-solving, analytical, and critical thinking skills.
 7. Strong comms and collaboration abilities, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
 8. Strong experience in AWS, ETL, Gen AI, MLOPS

Education:

 1. BS in the relevant field desired.
 2. Masters or PhD in relevant fields preferred but not required.

If you have proven experience in place of education, we are open to non-traditional pathways along with relevant certifications.

## Description

Work with internal teams and external vendors and partners to design, build, and deploy ML models to solve complex problems across state government, using techniques like supervised and unsupervised learning, deep learning, natural language processing, and computer vision. You will collaborate closely with data scientists/analysts/engineers, software engineers, subject matter experts, designers, and others. Responsibilities include:

 1. Prototyping, implementing, and optimizing ML algorithms and pipelines for scalability and performance.
 2. Integrating ML models into production systems, ensuring seamless deployment and monitoring.
 3. Collaborating with cross-functional teams to understand business requirements and translate them to technical solutions.
 4. Staying up-to-date with the latest developments in ML techniques, tools, and frameworks


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