
Lead AI ML Fin Ops
2 weeks ago
Welcome to Warner Bros. Discovery… the stuff dreams are made of.
Who We Are…
When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the
storytellers
bringing our characters to life, the
creators
bringing them to your living rooms and the
dreamers
creating what's next…
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
Your New Role
:
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
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**
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.
How We Get Things Done…
This last bit is probably the most important Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at
along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.
Championing Inclusion at WBD
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.
If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our
accessibility page
for instructions to submit your request.
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