Description : As the Lead AI / ML FinOps for one of the largest International Media & Entertainment companies, you will drive the financial optimization of AI / ML operations at scale, ensuring our systems are both cutting-edge and cost-efficient.
With AI / ML technologies playing a critical role in content creation, personalization, and audience engagement, your expertise will be instrumental in optimizing resource utilization, managing budgets, and implementing innovative cost-saving strategies.
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 youre excited by the challenge of combining deep technical expertise with strategic financial planning to create real-world impact, wed love to have you on board
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.
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.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.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.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 :
Bachelors or Masters 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 of experience in AI / ML operations, cloud cost optimization, or a related field, with a strong emphasis on financial planning and governance.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(ref : hirist.tech)