Job Description:
We are looking for a talented and motivated Mid-Level AI Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, natural language processing, and computer vision, along with hands-on experience in MLOps, model quantization, and various AI frameworks and libraries.
Key Responsibilities:
- Design, develop, and implement state-of-the-art machine learning models for various applications.
- Work on natural language processing (NLP) tasks such as text classification, sentiment analysis, and named entity recognition.
- Develop and optimize computer vision models for image and video analysis.
- Implement reinforcement learning algorithms to solve complex problems.
- Utilize MLOps best practices to streamline the deployment and monitoring of machine learning models.
- Perform model quantization to optimize performance on edge devices.
- Collaborate with cross-functional teams to integrate AI solutions into products and services.
- Conduct thorough research to stay updated with the latest trends and advancements in AI and machine learning.
- Develop and maintain RESTful APIs using FastAPI and Django for serving machine learning models.
- Write clean, maintainable, and efficient code using PyTorch, TensorFlow, pandas, and scikit-learn.
- Participate in code reviews, testing, and debugging to ensure high-quality software.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in AI/ML engineering or related roles.
- Proficiency in Python and experience with PyTorch and TensorFlow.
- Strong knowledge of NLP, reinforcement learning, and computer vision techniques.
- Experience with MLOps tools and practices.
- Familiarity with model quantization techniques.
- Hands-on experience with pandas, scikit-learn, and other data processing libraries.
- Good understanding of RESTful APIs and experience with FastAPI and Django.
- Excellent problem-solving skills and the ability to work independently as well as in a team.
- Strong research abilities to keep up with the fast-evolving AI landscape.
- Effective communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.
Preferred Qualifications:
Experience with cloud platforms such as AWS, Google Cloud, or Azure.
Knowledge of containerization and orchestration tools like Docker and Kubernetes.
Familiarity with CI/CD pipelines and version control systems like Git.
Contributions to open-source projects in the AI/ML domain.
