Job Title:  Senior Consultant | GEN AI | Bengaluru | SAP

Job Title: Senior Consultant – AI Launchpad & MLflow

Location: Pan India

Experience: 5 – 8 Years

Company: Deloitte

Job Summary:

Deloitte is seeking a Senior Consultant with 6–9 years of experience in AI/ML engineering, specifically working with platforms like AI Launchpad and MLflow. The candidate will be responsible for designing, developing, and deploying machine learning workflows, managing model lifecycles, and enabling end-to-end MLOps capabilities for enterprise clients.

Key Responsibilities:

• Lead the development and deployment of scalable AI/ML models using AI Launchpad tools and services.
• Implement MLflow to track experiments, manage model versions, and streamline deployment workflows.
• Build and automate machine learning pipelines for training, testing, and deploying models in production.
• Collaborate with data scientists, engineers, and business teams to translate business needs into ML solutions.
• Establish and maintain MLOps best practices including version control, reproducibility, model monitoring, and CI/CD for ML.
• Manage ML infrastructure, including computing environments, GPU instances, and cloud-based model registries.
• Ensure compliance with data privacy, security, and governance policies throughout the ML lifecycle.
• Provide technical leadership, mentor junior team members, and support stakeholder engagement.

Required Qualifications:

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

Experience:

• 5 – 8 years of experience in AI/ML solution development.
• Hands-on experience with AI Launchpad (or equivalent AI development platforms).
• Strong working knowledge of MLflow, including model tracking, versioning, and registry.
• Experience building ML models using Python, TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (Azure, AWS, or GCP) for model training and deployment.
• Strong understanding of MLOps practices and tools (e.g., Docker, Kubernetes, Git, CI/CD for ML).

Skills:

• Strong knowledge of machine learning model lifecycle and DevOps for ML.
• Proficiency in data manipulation and feature engineering using Pandas, NumPy, etc.
• Excellent communication and leadership skills.
• Strong analytical and problem-solving mindset.

Preferred Qualifications:

• Experience with Kubeflow, Databricks, SageMaker, or Vertex AI.
• Familiarity with model monitoring tools (e.g., Evidently, Fiddler).
• Certification in machine learning or cloud (e.g., Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty).
• Prior consulting experience or client-facing role.