Role: Full Stack Developer
Fully Remote
12 months contract on W2
Job description
Roles & Responsibilities:
AI/ML Development:
1. Model Development and Training:
Design develop and train machine learning models and algorithms to solve specific business problems.
Implement various machine learning techniques including supervised unsupervised and reinforcement learning.
2. Data Preprocessing and Analysis:
Perform data cleaning transformation and preprocessing to prepare data for model training.
Analyze and interpret complex data sets to identify patterns and trends.
3. Model Evaluation and Optimization:
Evaluate model performance using appropriate metrics and finetune models to improve accuracy and efficiency.
Implement model optimization techniques such as hyperparameter tuning and feature engineering.
4. Deployment and Maintenance:
Deploy machine learning models into production environments ensuring scalability and reliability.
Monitor and maintain models to ensure they continue to perform well over time.
Python Development:
Software Development:
Write clean maintainable and efficient Python code.
Develop and maintain Pythonbased applications APIs and microservices.
Code Review and Mentorship:
Conduct code reviews to ensure adherence to best practices and coding standards.
Mentor junior developers and provide guidance on best practices and development techniques.
Integration and Testing:
Integrate machine learning models with existing systems and applications.
Develop and execute unit tests integration tests and endtoend tests to ensure software quality.
Automation and Scripting:
Automate repetitive tasks and workflows using Python scripts.
Develop and maintain automation tools and frameworks.
Collaboration and Communication:
Collaborate with data scientists data engineers product managers and other stakeholders to understand requirements and deliver solutions.
Participate in design and architecture discussions to shape the direction of projects.
Documentation and Reporting:
Document code processes and methodologies to ensure knowledge sharing and maintainability.
Communicate findings progress and results to stakeholders through reports and presentations.
Continuous Learning and Improvement:
1. Stay Updated with Industry Trends:
Keep uptodate with the latest developments in AI/ML and Python technologies.
Experiment with new tools libraries and frameworks to improve existing solutions and processes.
2. Professional Development:
Attend conferences workshops and training sessions to enhance skills and knowledge.
Contribute to the AI/ML and Python developer communities through blogs talks and opensource contributions.
Problem Solving and Innovation:
1. Innovative Solutions:
Identify opportunities to apply AI/ML techniques to solve new and existing problems.
Propose and implement innovative solutions to improve business processes and outcomes.
2. Technical Challenges:
Tackle complex technical challenges and provide effective solutions.
Troubleshoot and resolve issues related to machine learning models and Python applications.
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