What are the responsibilities and job description for the Machine Learning Data Engineer position at Talent Groups?
Job Details
Job Title: Machine Learning Data Engineer
Location: Ft Worth TX
Duration: 4 Months contract to hire
Key Responsibilities:
Data Infrastructure & Pipeline Development
- Design, build, and maintain scalable and resilient data pipelines to support large-scale data processing.
- Develop backend systems to support the deployment and management of machine learning models and AI solutions.
- Ensure high availability, performance, and security of data infrastructure.
Machine Learning Model Deployment & Optimization
- Implement and automate ML model pipelines for seamless integration into production environments.
- Collaborate with data scientists and stakeholders to optimize model performance and ensure models are scalable and reliable.
- Monitor and refine deployed models to maintain accuracy and relevance.
Cross-Functional Collaboration
- Partner with business stakeholders, data scientists, and IT teams to define data needs and translate business requirements into technical solutions.
- Communicate findings and model performance to both technical and non-technical audiences through visualization tools and reports.
Basic Qualifications:
- Proficient in Python and SQL for data manipulation and model deployment.
- Experience building robust data pipelines and integrating ML models into production environments.
- Strong analytical and problem-solving skills; ability to work independently on complex analyses.
- Experience with data visualization tools such as Tableau or Power BI.
- Excellent verbal and written communication skills.
- Knowledge of ML frameworks and tools such as TensorFlow or PyTorch.
Preferred Qualifications:
- Bachelor s or master s degree in computer science, Data Science, Engineering, Analytics, or related field.
- 3 years of hands-on experience with ML, data engineering, and optimization solutions.
- Familiarity with PySpark and Databricks for distributed computing and scalable data processing.
- Knowledge of ML lifecycle management, model monitoring, and operationalization techniques.
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and CI/CD tools such as Jenkins, GitLab CI.
- Understanding of deep learning model development and deployment strategies.
- Familiarity with CLIENTS reporting systems (e.g., DPR, SCORE, Corporate Dashboard) is a strong plus.
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.
Salary : $60 - $70
