AI/ML Engineer

Job Summary: As an AI/ML Engineer at CoRover, you will play a crucial role in designing, developing, and deploying advanced machine learning models and AI systems. You will collaborate with cross-functional teams to drive the development of innovative solutions and ensure our technology remains at the cutting edge.

Key Responsibilities:

• Model Development: Create, train, and fine-tune machine learning models and algorithms to address complex challenges and improve our products and services.
• Data Handling: Collect, preprocess, and analyze large datasets to extract meaningful insights and optimize model performance.
• Innovation: Stay abreast of the latest AI/ML research and trends, applying new techniques and methodologies to enhance our solutions.
• Collaboration: Work closely with data scientists, software engineers, and product managers to integrate AI/ML models into our systems and ensure seamless implementation.
• Deployment: Deploy and maintain machine learning models in production environments, ensuring their scalability, reliability, and efficiency.
• Troubleshooting: Identify and resolve issues related to AI/ML models and performance, continually seeking improvements.
• Documentation: Develop comprehensive documentation for models, processes, and methodologies to facilitate knowledge sharing and project continuity.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
• Experience: 0-2 years of experience in AI/ML engineering or a related role, with a proven track record of successful projects involving machine learning and artificial intelligence.
• Technical Skills:
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of data analysis, statistical methods, and feature engineering.
  • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for model deployment and management.
  • Knowledge of version control systems (e.g., Git) and collaboration tools (e.g., JIRA).
• Soft Skills:
  • Excellent problem-solving abilities and the capability to work independently as well as part of a team.
  • Strong communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with deep learning, natural language processing, or computer vision.
• Knowledge of Agile methodologies and software engineering best practices.
• Contributions to open-source projects or publications in AI/ML research.