AI/ML Engineer

Job Description : 

• Application Development: Design, develop, and deploy applications utilizing Large Language Models (LLMs) like OpenAI GPT.
• MLOps Pipeline Management: Build and maintain Machine Learning Operations (MLOps) pipelines, encompassing data ingestion,
• Chunking, vectorization, feature engineering, model training, deployment, and monitoring.
• Cloud Platform Utilization: Leverage cloud platforms such as AWS, GCP, or Azure for machine learning model development, training, and deployment.
• Workflow Automation: Implement DevOps/MLOps/LLMOps best practices to automate machine learning workflows and enhance efficiency.
• Performance Monitoring: Develop and implement monitoring systems to track model performance and identify issues.
• Collaboration: Work closely with data scientists, engineers, and product teams to deliver machine learning solutions.

AI/ML

Key Responsibilities:

• Design, develop, and deploy scalable AI/ML models using Python and associated libraries (TensorFlow, PyTorch, Scikit-learn, etc.).
• Collaborate with data scientists, engineers, and product managers to define and prioritize AI-driven solutions to business problems.
• Implement and optimize algorithms for classification, regression, clustering, and deep learning models.
• Build and maintain end-to-end machine learning pipelines, from data preprocessing to model deployment in production environments (cloud and on-premise).
• Perform model evaluation, tuning, and validation to ensure optimal performance and generalization.
• Integrate machine learning models with existing software applications or frameworks, ensuring seamless operation and efficiency.
• Utilize MLOps tools to automate model versioning, monitoring, and retraining for continuous improvement.
• Mentor junior engineers and data scientists, promoting knowledge sharing and development best practices.
• Stay updated on the latest advancements in AI/ML and integrate new tools and techniques into current processes.
• Conduct research and experimentation to solve complex problems and improve current AI models and algorithms.

Required Skills and Qualifications:

• 4+ years of hands-on experience in AI/ML development, including real-world deployment of machine learning models.
• Expert-level proficiency in Python programming and associated AI/ML libraries such as TensorFlow, PyTorch, Keras, and Scikit-learn.
• Strong understanding of deep learning, neural networks, natural language processing (NLP), computer vision, and traditional machine learning algorithms.
• Experience in deploying AI/ML models in production environments using cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Proficient in working with large datasets, data wrangling, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib.
• Knowledge of database systems (SQL, NoSQL) and experience with distributed computing frameworks like Spark.
• Strong problem-solving skills and the ability to translate business requirements into technical solutions.
• Familiarity with MLOps best practices, including CI/CD pipelines, model monitoring, version control, and automated retraining.
•  Excellent written and verbal communication skills and the ability to work in a collaborative, agile environment.
• Experience with tools like Git, Jupyter Notebooks, and CI/CD tools (Jenkins, CircleCI).