1. Algorithm Development: Collaborate with data scientists and researchers to design and develop machine learning algorithms and models for various applications.
2. Data Preprocessing: Prepare and preprocess datasets, including data cleaning, feature extraction, and transformation, to ensure data quality for model training.
3. Model Implementation: Implement machine learning models using programming languages such as Python and relevant machine learning frameworks.
4. Model Training and Evaluation: Train machine learning models using diverse datasets, evaluate model performance using appropriate metrics, and fine-tune models as needed.
5. Feature Engineering: Engage in feature engineering to extract relevant features from raw data, enhancing model performance and predictive capabilities.
6. Deployment: Collaborate with software engineers to deploy machine learning models into production environments, ensuring scalability and efficiency.
7. Documentation: Provide clear and organized documentation for machine learning solutions, facilitating collaboration and knowledge sharing.
8. Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and domain experts, to integrate machine learning solutions into larger projects.
9. Stay Abreast of Trends: Stay updated on the latest advancements in machine learning research and technologies, incorporating best practices and innovative techniques.
10. Problem Solving: Apply analytical and problem-solving skills to address challenges related to data quality, model performance, and algorithm optimization.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Minimum of 3-5 years of experience as a Machine Learning Engineer or in a similar role, with practical experience in developing and implementing machine learning models.
• Proficiency in programming languages such as Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of machine learning algorithms, supervised and unsupervised learning techniques, and neural networks.
• Experience with data preprocessing, feature engineering, and data manipulation libraries (e.g., NumPy, pandas).
• Knowledge of version control systems (e.g., Git) and software engineering principles is a plus.
• Strong analytical and problem-solving skills for addressing challenges in machine learning development.
• Effective communication skills to collaborate with cross-functional teams and convey technical concepts.
• Passion for staying updated on machine learning trends and emerging technologies.

Benefits:

• Competitive salary with growth opportunities.
• Comprehensive health, dental, and vision insurance plans.
• Retirement savings plan with company contributions.
• Ongoing professional development and training opportunities.
• Flexible work arrangements, including remote work options.
• Collaborative and innovative work environment in the machine learning and technology sector.
• Opportunities for career advancement within a dynamic machine learning-focused organization.

If you are an experienced Machine Learning Engineer with a passion for developing innovative solutions, implementing machine learning models, and staying updated on machine learning trends, we encourage you to apply. Join AI Solutions Group and contribute to our mission of delivering transformative machine learning solutions for diverse industries.