AI/ML Engineer Devi Technologies

Devitechs; Town of Texas (WI); On-site; USD 80,000 - 120,000; Full time

Job summary

A machine learning solutions provider seeks a skilled professional to design, develop, and deploy machine learning models. The role requires collaboration with engineers to integrate AI solutions, ensure performance in production, and maintain documentation. Candidates should have experience in data cleaning, model optimization, and using frameworks like TensorFlow and PyTorch. The ideal applicant has strong skills in both machine learning and team collaboration, making them capable of mentoring junior members and improving project outcomes.

Qualifications

• Experience in designing, developing, and deploying machine learning models.
• Ability to work with large datasets and perform data preprocessing.
• Strong understanding of model evaluation metrics and validation techniques.

Responsibilities

• Design, develop, and deploy machine learning models for real-world applications.
• Collaborate with data engineers and software developers.
• Optimize models for speed, scalability, and efficiency.

Skills

Machine learning

Data cleaning

Predictive modeling

Deep learning

Natural language processing

Feature engineering

Cloud deployment

Team collaboration

Tools

TensorFlow

PyTorch

Scikit-learn

Job description

• Design, develop, and deploy machine learning models for real-world applications. Ensure models are scalable, reliable, and optimized for production environments.
• Work with large structured and unstructured datasets from multiple sources. Perform data cleaning, transformation, and preprocessing for analysis readiness.
• Build predictive, classification, and recommendation models. Continuously improve model accuracy through experimentation and tuning.
• Collaborate with data engineers and software developers. Integrate AI solutions seamlessly into existing systems and workflows.
• Deploy models using cloud platforms and monitor performance. Ensure consistent behavior in live production environments.
• Implement deep learning and natural language processing solutions. Enhance automation and intelligent decision‑making capabilities.
• Perform feature engineering to improve model effectiveness. Analyze patterns and correlations in complex datasets.
• Use frameworks like TensorFlow, PyTorch, and Scikit-learn. Develop reusable and scalable machine learning pipelines.
• Evaluate models using appropriate metrics and validation techniques. Ensure robustness and generalization of results.
• Automate training, testing, and deployment pipelines. Improve efficiency and reduce manual intervention.
• Collaborate with stakeholders to understand business requirements. Translate business problems into technical AI solutions.
• Maintain clear and comprehensive documentation of models. Support knowledge sharing and future development.
• Troubleshoot model and pipeline issues. Implement fixes and optimize performance.
• Ensure compliance with data privacy and ethical AI standards. Implement responsible AI practices across projects.
• Optimize models for speed, scalability, and efficiency. Improve inference time and system throughput.
• Participate in code reviews and technical discussions. Maintain high‑quality coding and development standards.
• Support integration of AI features into applications. Ensure seamless user experience and functionality.
• Stay updated with the latest AI trends and technologies. Adopt best practices and innovative approaches.
• Conduct experiments and A/B testing. Validate the effectiveness of deployed AI solutions.
• Mentor junior team members and provide technical guidance. Contribute to team growth and knowledge development.