Job Title: AI Engineer
Job Summary
We are seeking an innovative AI Engineer to develop and deploy cutting-edge artificial intelligence and machine learning models that automate processes, generate valuable insights, and enhance user experiences. The ideal candidate will bridge the gap between data science and software engineering, bringing AI prototypes to life in a scalable production environment.
Key Responsibilities
- Design, develop, and implement AI models and algorithms to solve complex business challenges (e.g., computer vision, NLP, predictive analytics).
- Collaborate with data scientists and software engineers to transition models from research/prototypes to scalable production environments.
- Build and maintain robust, scalable machine learning pipelines for data ingestion, transformation, and model retraining.
- Deploy AI solutions into cloud platforms (AWS, Azure, GCP) using MLOps practices and containerization tools like Docker and Kubernetes.
- Monitor, test, and optimize the performance, accuracy, and efficiency of deployed AI models, troubleshooting issues as they arise.
- Ensure AI systems are secure, ethical, and meet performance requirements, documenting system behavior, inputs, and outputs.
- Stay current with the latest advancements, research papers, and tools in AI/ML, integrating new technologies where relevant (e.g., Generative AI, LLMs, RAG).
- Communicate effectively with cross-functional teams and stakeholders to translate AI capabilities into tangible business value.
Required Skills and Qualifications
- Experience: Proven hands-on experience in building, training, and deploying ML models in a production setting.
- Programming Proficiency: Expertise in programming languages such as Python, Java, or C++.
- ML Frameworks & Tools: Experience with ML frameworks and libraries
- Cloud & MLOps: Familiarity with cloud computing platforms (AWS, Azure, Google Cloud) and MLOps tools
- Technical Knowledge: Strong understanding of machine learning algorithms, neural networks, deep learning techniques, and data analysis.
- Soft Skills: Excellent problem-solving, analytical, and communication skills; ability to work collaboratively in a team environment.
Preferred Qualifications
- Experience with specific AI domains like Natural Language Processing (NLP), computer vision, or reinforcement learning.
- Knowledge of big data technologies like Hadoop or Spark.
- Familiarity with database design (SQL and NoSQL) and API development.