Quanteon Solutions - AI/ML Engineer - NLP/Deep Learning

Description

Key Responsibilities

• Design, develop, and deploy machine learning, deep learning, and NLP models for diverse business applications.
• Build end-to-end ML pipelines covering data preprocessing, feature engineering, model training, evaluation, and deployment.
• Optimize model performance and ensure scalability and reliability in production environments.
• Collaborate with data scientists, product managers, and engineering teams to convert business requirements into technical AI solutions.
• Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights.
• Implement MLOps best practices for model versioning, monitoring, CI/CD, and automated workflows.
• Stay updated with the latest advancements in AI/ML tools, frameworks, and research; evaluate their applicability.
• Document the overall system architecture, model design decisions, and development processes.
  

Required Skills & Expertise

• Strong programming experience in Python and libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, and Keras.
• Proven experience in building, training, and deploying ML/DL models in production environments.
• Solid understanding of machine learning algorithms, neural networks, NLP, and basic computer vision concepts.
• Experience working with REST APIs, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
• Familiarity with MLOps tools such as MLflow, Airflow, DVC, Kubeflow, or similar frameworks.
• Understanding of data pipelines and exposure to big data technologies like Spark or Hadoop (preferred).
• Strong analytical and problem-solving abilities with the ability to handle large datasets.
• Excellent communication skills and ability to work in cross-functional teams.
  

Preferred Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, AI, Machine Learning, or related fields.
• Experience deploying ML models using cloud services such as AWS SageMaker, GCP Vertex AI, or Azure ML.
• Hands-on experience in LLM fine-tuning, Generative AI, or working with Large Language Models.
• Exposure to computer vision projects or advanced NLP applications.