We are seeking an experienced AI/ML Engineer with 45 years of hands-on expertise in designing, developing, and deploying scalable machine learning and AI-driven solutions. The ideal candidate will have strong proficiency in model development, data engineering, MLOps, and cloud deployment, with the ability to collaborate across teams and translate business needs into advanced AI solutions.

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.