Senior Project Manager

Hi, We need early joiners for Senior project Manager. Exp-10+ years Location-Bangalore Please find below JD- Job Description: We are seeking a highly skilled and experienced Project Manager specializing in MLOps (Machine Learning Operations) to lead a large-scale, high-impact project focused on the deployment, management, and optimization of machine learning models at the enterprise scale. The ideal candidate will have a strong technical background, coupled with excellent leadership, communication, and project management skills, capable of managing multiple stakeholders and ensuring successful project execution from inception to completion. Key Responsibilities:

1. Project Leadership and Strategy:

• Lead and manage all phases of the MLOps project lifecycle, including planning, execution, monitoring, and delivery.
• Develop and implement a detailed project roadmap, ensuring that all milestones are achieved on time and within budget.
• Coordinate cross-functional teams (data scientists, machine learning engineers, DevOps, IT, business stakeholders) to ensure alignment on goals and deliverables.

1. Stakeholder Management:

• Act as the primary point of contact for internal and external stakeholders, including senior management, technical teams, and business units.
• Regularly update stakeholders on project status, risks, and mitigation strategies.
• Foster collaboration across teams to ensure smooth communication and efficient workflow.

1. MLOps Implementation:

• Oversee the deployment of ML models into production environments and ensure smooth integration with existing systems and infrastructure.
• Implement best practices for MLOps pipelines, including version control, model training, testing, monitoring, and model retraining.
• Lead efforts for model monitoring, logging, and performance tracking to ensure models are performing as expected post-deployment.

1. Risk and Issue Management:

• Proactively identify potential risks or roadblocks to project success and implement mitigation plans.
• Escalate critical issues to appropriate stakeholders when necessary, ensuring timely resolution.

1. Quality Assurance:

• Ensure the overall quality of the MLOps processes by maintaining high standards for model performance, reproducibility, and efficiency.
• Define and enforce clear standards for model validation, testing, and deployment to ensure consistency and reliability in production

1. Budget and Resource Management:

• Oversee project budgeting, resource allocation, and ensure that the team has the necessary tools, technologies, and support to execute the project successfully.
• Monitor and report on budget usage, providing forecasts and justifications as necessary

1. Continuous Improvement:

• Identify and implement process improvements in the MLOps pipeline and project management methodologies.
• Keep up to date with the latest industry trends, technologies, and tools in the MLOps space to ensure that the project benefits from state-of-the-art practices.

1. Documentation and Reporting:

• Ensure thorough documentation of all project deliverables, processes, and decision-making.
• Create detailed project reports for both technical and non-technical stakeholders, ensuring transparency in progress, challenges, and outcomes.

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field. PMP, Scrum Master, or similar certifications preferred.