Description
About the Role:
We are seeking a highly skilled and experienced AI/ML Engineer to join our innovative team. The ideal candidate will bring a wealth of knowledge and a proven track record in implementing complex machine-learning projects. As an AI/ML Engineer, you will leverage cutting-edge tools and technologies to design, build, and deploy machine learning models that drive business value. You will be involved in the full lifecycle of machine learning projects, from ideation and data exploration to deployment and performance monitoring.
Key Responsibilities:
- Develop, implement, and maintain scalable machine learning models to solve complex business problems.
- Collaborate with cross-functional teams to understand and solve real-world challenges.
- Analyze large and diverse datasets to derive actionable insights and improve model performance.
- Deploy machine learning models using industry-standard practices to production environments.
- Stay current with the latest advancements in AI/ML and incorporate modern techniques and tools into projects.
- Optimize algorithms for performance and scalability.
- Mentor and guide junior team members, fostering a culture of continuous learning and improvement.
- Create robust, reproducible prototypes that demonstrate a high potential to add value to the business.
Key Requirements:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
- Proven experience of + years in developing and deploying machine learning models in production settings.
- Strong programming skills in Python or R, with specific expertise in libraries such as TensorFlow, PyTorch, or Scikit-learn.
- Significant experience with data preprocessing and analysis using tools like Pandas and NumPy.
- Expertise in cloud computing services such as AWS, Azure, or Google Cloud Platform for deploying models.
- Familiarity with SQL and NoSQL databases for handling large datasets.
- Experience using modern development practices such as Git for version control and Jupyter Notebooks for literate programming.
Good-to-Have Skills:
- Hands-on experience with MLOps frameworks and tools such as MLflow or Kubeflow.
- Understanding and practical experience with NLP, computer vision, or time-series forecasting.
- Familiarity with containerization technologies like Docker.
- Certification in AI/ML from a recognized institution.
- Familiarity with big data processing frameworks like Apache Spark or Hadoop.
Must-Have Skills:
- Excellent problem-solving abilities and attention to detail.
- Strong communication skills to effectively present technical concepts to non-technical stakeholders.
- Proficiency in deploying models in production environments and maintaining them.
- A proactive approach to learning and implementing new AI/ML technologies.