Overview Of The Company
Fox Corporation
Under the FOX banner, we produce and distribute content through some of the world’s leading and most valued brands, including: FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations and Tubi Media Group. We empower a diverse range of creators to imagine and develop culturally significant content, while building an organization that thrives on creative ideas, operational expertise and strategic thinking.
Job Description
As a Staff Software Engineer, you will play a pivotal role in the development of innovative AI applications, services, and tools. You will leverage your extensive experience in applying AI/ML to drive business value, thrive in our fast-paced environment, and contribute to the advancement of emerging technologies. Your past experience in digital media and video will be instrumental in building dynamic workflows and orchestrations for both live and VOD (Video on Demand) content. Your expertise in multi-cloud environments such as AWS, GCP, and Databricks will be crucial in our distributed computing landscape. We work on cutting edge projects using AI that includes building conversational agents using LLMs, generating automatic highlights, contextualizing videos and articles at scale, driving live storytelling, powering bleeding edge consumer products and features.
If you are passionate about building the future of AI applications and have the expertise to thrive in a dynamic and fast-paced environment, we would love to hear from you!
A Snapshot Of Your Responsibilities
- AI at Scale: Design and implement novel and scalable AI solutions for real business problems
- Develop Dynamic Workflows: Design and implement workflows to generate and manage assets for live streaming and VOD
- Prototype and Scale Solutions: Prototype new approaches and productionize solutions at scale for hundreds of millions of active users
- Maintain Craftsmanship: Uphold high standards of software craftsmanship while delivering impactful results
- Provide Expert Guidance: Offer expert advice to engineering teams and project leaders to navigate technical challenges
- Cultivate Inclusive Culture: Instill an innovative and collaborative culture within your team and the broader organization
- Ensure Quality Outputs: Ensure your team produces consistently trustworthy and high-quality technical outputs that influence the business
- Collaborate Effectively: Work closely with peers, engineering leadership, and product management to drive project success
- Promote ML Best Practices: Role-model and promote best practices of ML model development, testing, and evaluation throughout the organization
- Engage with ML Practitioners: Be part of an active group of machine learning practitioners across the organization.
What You Will Need
- Software Engineering Experience: Proven experience in software engineering, data science, and ML engineering
- Media Streaming Expertise: Strong background in live media streaming and handling VOD content
- Gen AI: Strong understanding of generative AI technologies and their underlying mechanisms
- Prompt Engineering: Develop and refine creative writing prompts to guide our generative AI in producing relevant and engaging content
- Vector Database Proficiency: Experience working with vector databases
- API Design: Proficient in designing REST or GraphQL APIs
- ML Systems at Scale: Hands-on experience implementing production NLP and ML systems at scale using Python, Java, Scala, or similar languages
- ML Frameworks: Experience with TensorFlow, PyTorch etc.
- Distributed Systems Design: Solid understanding of designing distributed systems
- Data Pipelines: Proficient with building batch and streaming data pipelines on cloud platforms.
NICE TO HAVE, BUT NOT A DEALBREAKER
- ML for Media: Experience leveraging machine learning techniques for live and VOD assets
- Search Clusters: Capable of designing and implementing search clusters using OpenSearch or Elasticsearch
- AI Ethics: Familiarity with AI ethics, including understanding and mitigating biases in AI outputs
- Software Design Patterns: Deep understanding of software design patterns and domain-driven design
- Academic Excellence: Relevant academic work or research in AI/ML, software engineering, or related fields
- Agile Processes: Passion for agile software processes, data-driven development, reliability, and disciplined experimentation
- Research Engagement: Regularly survey research publications in machine learning and software engineering communities
- Customer Focus: A passion for understanding and serving customers' needs, ensuring their satisfaction and success.
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