

AI ENGINEER
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer on a long-term contract in Richardson, TX (Hybrid). Requires 4+ years in AI/ML engineering, proficiency in Python, cloud AI services, and strong ML algorithm knowledge. Familiarity with MLOps and database management is essential.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
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ποΈ - Date discovered
August 14, 2025
π - Project duration
Unknown
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Richardson, TX
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π§ - Skills detailed
#Kubernetes #Monitoring #Scala #AWS (Amazon Web Services) #Deployment #TensorFlow #Data Engineering #"ETL (Extract #Transform #Load)" #Python #Spark (Apache Spark) #Deep Learning #GCP (Google Cloud Platform) #Pandas #AI (Artificial Intelligence) #SageMaker #Kafka (Apache Kafka) #Docker #NoSQL #Databricks #ML (Machine Learning) #Compliance #Cloud #NumPy #NLP (Natural Language Processing) #AWS SageMaker #PyTorch #Libraries #Azure Machine Learning #SQL (Structured Query Language) #Datasets #Azure #Databases #Data Science #Neural Networks
Role description
Job Title: AI Engineer
Location: Richardson, TX ||Hybrid
Employment Type: Long-term Contract
Job Summary:
We are looking for a talented AI Engineer to design, develop, and deploy artificial intelligence and machine learning solutions for enterprise-scale applications. The ideal candidate will have strong expertise in ML model development, data engineering, and cloud-based AI services, with the ability to work across the full AI/ML lifecycleβfrom data preparation to production deployment.
Key Responsibilities:
β’ Design, develop, and train machine learning (ML) and deep learning (DL) models.
β’ Preprocess, clean, and transform structured and unstructured datasets for modeling.
β’ Implement, test, and optimize algorithms for performance, scalability, and accuracy.
β’ Deploy AI/ML models into production environments using cloud-based services (Azure/AWS/GCP).
β’ Work closely with data scientists, data engineers, and software developers to integrate AI solutions into applications.
β’ Monitor model performance and retrain or fine-tune as needed to maintain accuracy over time.
β’ Research and experiment with new AI frameworks, tools, and techniques to improve solutions.
β’ Document models, workflows, and deployment processes for maintainability and compliance.
Required Skills & Qualifications:
β’ 4+ years of experience in AI/ML engineering or applied data science.
β’ Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
β’ Strong understanding of ML algorithms, neural networks, NLP, and computer vision concepts.
β’ Experience with cloud AI/ML services (Azure Machine Learning, AWS SageMaker, GCP Vertex AI).
β’ Familiarity with MLOps practices, including CI/CD for ML and model monitoring.
β’ Proficiency in working with SQL and NoSQL databases.
β’ Strong problem-solving and analytical skills.
Nice-to-Have:
β’ Experience with LLMs (Large Language Models) and generative AI solutions.
β’ Exposure to data engineering tools like Spark, Databricks, or Kafka.
β’ Knowledge of containerization (Docker) and orchestration (Kubernetes) for AI workloads.
Job Title: AI Engineer
Location: Richardson, TX ||Hybrid
Employment Type: Long-term Contract
Job Summary:
We are looking for a talented AI Engineer to design, develop, and deploy artificial intelligence and machine learning solutions for enterprise-scale applications. The ideal candidate will have strong expertise in ML model development, data engineering, and cloud-based AI services, with the ability to work across the full AI/ML lifecycleβfrom data preparation to production deployment.
Key Responsibilities:
β’ Design, develop, and train machine learning (ML) and deep learning (DL) models.
β’ Preprocess, clean, and transform structured and unstructured datasets for modeling.
β’ Implement, test, and optimize algorithms for performance, scalability, and accuracy.
β’ Deploy AI/ML models into production environments using cloud-based services (Azure/AWS/GCP).
β’ Work closely with data scientists, data engineers, and software developers to integrate AI solutions into applications.
β’ Monitor model performance and retrain or fine-tune as needed to maintain accuracy over time.
β’ Research and experiment with new AI frameworks, tools, and techniques to improve solutions.
β’ Document models, workflows, and deployment processes for maintainability and compliance.
Required Skills & Qualifications:
β’ 4+ years of experience in AI/ML engineering or applied data science.
β’ Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
β’ Strong understanding of ML algorithms, neural networks, NLP, and computer vision concepts.
β’ Experience with cloud AI/ML services (Azure Machine Learning, AWS SageMaker, GCP Vertex AI).
β’ Familiarity with MLOps practices, including CI/CD for ML and model monitoring.
β’ Proficiency in working with SQL and NoSQL databases.
β’ Strong problem-solving and analytical skills.
Nice-to-Have:
β’ Experience with LLMs (Large Language Models) and generative AI solutions.
β’ Exposure to data engineering tools like Spark, Databricks, or Kafka.
β’ Knowledge of containerization (Docker) and orchestration (Kubernetes) for AI workloads.