AI/MLOps Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/MLOps Engineer on a long-term contract in Richardson, TX (Hybrid). Requires 4+ years in AI/ML engineering, proficiency in Python, cloud AI services, and MLOps practices. Experience with LLMs and data engineering tools is a plus.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 27, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Richardson, TX
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🧠 - Skills detailed
#Databases #Cloud #Spark (Apache Spark) #Datasets #Databricks #Pandas #NoSQL #NLP (Natural Language Processing) #ML (Machine Learning) #Azure Machine Learning #PyTorch #Compliance #SageMaker #AI (Artificial Intelligence) #Deep Learning #Kafka (Apache Kafka) #AWS (Amazon Web Services) #Libraries #SQL (Structured Query Language) #AWS SageMaker #Docker #Data Engineering #NumPy #Monitoring #Deployment #Kubernetes #Azure #Data Science #Python #Scala #"ETL (Extract #Transform #Load)" #TensorFlow #GCP (Google Cloud Platform) #Neural Networks
Role description
Job Title:AI/MLOps 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 lifecycle—from data preparation to production deployment.
Key Responsibilities:
• Design, develop, and train machine learning (ML) and deep learning (DL) models.
• Preprocess, clean, and transform structured and unstructured datasets for modeling.
• Implement, test, and optimize algorithms for performance, scalability, and accuracy.
• Deploy AI/ML models into production environments using cloud-based services (Azure/AWS/GCP).
• Work closely with data scientists, data engineers, and software developers to integrate AI solutions into applications.
• Monitor model performance and retrain or fine-tune as needed to maintain accuracy over time.
• Research and experiment with new AI frameworks, tools, and techniques to improve solutions.
• Document models, workflows, and deployment processes for maintainability and compliance.
Required Skills & Qualifications:
• 4+ years of experience in AI/ML engineering or applied data science.
• Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
• Strong understanding of ML algorithms, neural networks, NLP, and computer vision concepts.
• Experience with cloud AI/ML services (Azure Machine Learning, AWS SageMaker, GCP Vertex AI).
• Familiarity with MLOps practices, including CI/CD for ML and model monitoring.
• Proficiency in working with SQL and NoSQL databases.
• Strong problem-solving and analytical skills.
Nice-to-Have:
• Experience with LLMs (Large Language Models) and generative AI solutions.
• Exposure to data engineering tools like Spark, Databricks, or Kafka.
• Knowledge of containerization (Docker) and orchestration (Kubernetes) for AI workloads.
Job Title:AI/MLOps 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 lifecycle—from data preparation to production deployment.
Key Responsibilities:
• Design, develop, and train machine learning (ML) and deep learning (DL) models.
• Preprocess, clean, and transform structured and unstructured datasets for modeling.
• Implement, test, and optimize algorithms for performance, scalability, and accuracy.
• Deploy AI/ML models into production environments using cloud-based services (Azure/AWS/GCP).
• Work closely with data scientists, data engineers, and software developers to integrate AI solutions into applications.
• Monitor model performance and retrain or fine-tune as needed to maintain accuracy over time.
• Research and experiment with new AI frameworks, tools, and techniques to improve solutions.
• Document models, workflows, and deployment processes for maintainability and compliance.
Required Skills & Qualifications:
• 4+ years of experience in AI/ML engineering or applied data science.
• Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
• Strong understanding of ML algorithms, neural networks, NLP, and computer vision concepts.
• Experience with cloud AI/ML services (Azure Machine Learning, AWS SageMaker, GCP Vertex AI).
• Familiarity with MLOps practices, including CI/CD for ML and model monitoring.
• Proficiency in working with SQL and NoSQL databases.
• Strong problem-solving and analytical skills.
Nice-to-Have:
• Experience with LLMs (Large Language Models) and generative AI solutions.
• Exposure to data engineering tools like Spark, Databricks, or Kafka.
• Knowledge of containerization (Docker) and orchestration (Kubernetes) for AI workloads.
