Lead AI ML Fin Ops

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Lead – AI/ML FinOps

Based in India, you will lead the charge in setting up and evolving a robust AI/ML financial operations framework, collaborating closely with engineering, data science, and finance teams. This role is perfect for someone passionate about AI/ML technology and operational excellence, with a strong focus on financial stewardship. If you’re excited by the challenge of combining deep technical expertise with strategic financial planning to create real-world impact, we’d love to have you on board

1. AI/ML Financial Planning and Cost Optimization

• Develop and implement strategies to optimize the cost of AI/ML workloads across cloud and on-premise environments. 

• Analyze and forecast AI/ML resource consumption, creating actionable insights to drive financial efficiency. 

• Establish KPIs and benchmarks for AI/ML operational costs, ensuring alignment with budgetary goals. 

• Collaborate with cloud vendors to negotiate contracts and optimize pricing models for AI/ML services. 

• Identify opportunities for cost reduction through model performance improvements, workload optimizations, and better infrastructure management. 

2. Cloud and Infrastructure Cost Management

• Lead initiatives to optimize cloud resource allocation for AI/ML workloads, ensuring scalability and efficiency. 

• Monitor and manage the financial impact of AI/ML resource utilization, leveraging tools like FinOps platforms and custom analytics dashboards. 

• Drive adoption of cost-aware practices across teams, promoting efficient use of compute, storage, and networking resources. 

• Establish governance policies to prevent cost overruns and ensure compliance with organizational financial guidelines. 

• Recommend strategies for multi-cloud and hybrid-cloud deployments to achieve cost and performance objectives. 

3. Collaboration and Stakeholder Engagement

• Partner with data science, engineering, and product teams to align AI/ML operational goals with business priorities. 

• Work closely with finance and procurement teams to streamline budgeting, reporting, and approval processes for AI/ML initiatives. 

• Act as a bridge between technical teams and business leaders, ensuring clear communication of financial trade-offs and benefits. 

• Build strong relationships with cloud service providers to leverage their expertise and tools for cost optimization. 

• Advocate for financial best practices within AI/ML operations, fostering a culture of accountability and cost-conscious innovation. 

4. AI/ML Workflow and Lifecycle Management

• Oversee the end-to-end lifecycle of AI/ML models, focusing on efficient resource usage during development, training, and deployment phases. 

• Implement cost-aware model retraining schedules based on business needs and performance thresholds. 

• Collaborate with MLOps teams to streamline model deployment pipelines, reducing operational overheads. 

• Monitor and analyze the financial impact of different AI/ML use cases to prioritize high-value projects. 

• Develop processes to decommission obsolete models and infrastructure to avoid unnecessary expenditures. 

5. Innovation and Continuous Improvement

• Stay updated on emerging technologies and trends in AI/ML FinOps, leveraging innovations to enhance cost efficiency. 

• Lead the evaluation and adoption of tools and frameworks for AI/ML cost monitoring and optimization. 

• Promote a mindset of continuous improvement, encouraging teams to experiment with cost-effective methodologies. 

• Drive internal knowledge-sharing sessions to disseminate best practices in AI/ML financial management. 

• Collaborate on global initiatives to standardize and improve AI/ML FinOps practices across the organization. 

Qualifications & Experiences: 

Academic Qualifications:

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

• Specialized certifications in FinOps, Cloud Cost Management, or AI/ML technologies are highly desirable. 

Professional Experience:

• 6+ years

• Proven track record of managing AI/ML workloads in cloud environments such as AWS, Azure, or Google Cloud. 

• Extensive experience in building and implementing FinOps strategies for large-scale AI/ML projects. 

• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and their computational requirements. 

• Expertise in budgeting, cost forecasting, and financial modeling for technology initiatives. 

Technical Skills:

• Proficiency in cloud cost management tools like AWS Cost Explorer, Azure Cost Management, or third-party solutions (e.g., CloudHealth, Apptio). 

• Strong understanding of AI/ML infrastructure, including GPUs, TPUs, and distributed computing architectures. 

• Experience in automating financial reporting and monitoring using analytics tools and scripts (e.g., Python, SQL). 

• Knowledge of MLOps practices and tools, including CI/CD pipelines, model monitoring, and version control. 

• Strong data analysis skills to identify cost-saving opportunities and drive actionable insights. 

Other Skills:

• Excellent leadership and communication skills, with the ability to influence stakeholders across levels. 

• Strong problem-solving and analytical abilities, with a focus on financial impact and operational efficiency. 

• Proactive mindset, with a passion for innovation and continuous improvement. 

• Proven ability to work collaboratively in a cross-functional and dynamic environment. 

• Strong organizational skills, with the ability to manage multiple priorities and deliver results under tight deadlines. 

How We Get Things Done…