Description

You will build and deploy advanced AI and machine learning solutions.

Responsibilities

• Develop and optimize predictive and prescriptive models using supervised and unsupervised learning.
• Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation.
• Utilize MLOps to deploy, monitor, and maintain ML models in production.
• Design and develop data pipelines for large-scale ETL processing in collaboration with data engineers.
• Communicate complex methodology, results, and business insights to technical and non-technical stakeholders.

Required Skills

• 5+ years of experience in Data Science, Machine Learning, or related fields.
• Strong expertise in Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
• Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment.
• Proficiency in cloud platforms (AWS/GCP) and scalable data engineering.
• Strong understanding of probability theory, statistics, and experimental design (A/B Testing).
• Experience with collaborative software engineering practices (Agile, DevOps).
• Proficiency in ETL processes and CI/CD workflows.
• Bachelor's or Master’s degree in Computer Science, Mathematics, Engineering, or related field.

Preferred Skills

• Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI.
• Experience with Knowledge Graphs and their integration into AI/ML pipelines.

Key Skills

Education

Bachelor's or Master's degrees