Senior Staff Machine Learning Engineer

Posted 2 Days Ago
New York, NY
Hybrid
160K-296K Annually
Senior level
Artificial Intelligence • Digital Media • Gaming • Machine Learning • News + Entertainment • Software
The Role
The Senior Staff Machine Learning Engineer will lead the design, research, and evaluation of ML models and systems at CNN. Responsibilities include working with NLP, recommendation systems, and Large Language Models, mentoring, collaborating on ML projects, and ensuring best practices in model training and deployment.
Summary Generated by Built In

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.
We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN.
To see what it's like to work at CNN, follow @WBDLife on Instagram and X!
About the Team
The Machine Learning team at CNN Digital is dedicated to research, build and evaluate Machine Learning and AI capabilities at CNN. The team is comprised of talented ML Engineers, Data Scientists and ML Platform Engineers. Our current production ML products include Article recommendations, Video recommendations, Related Content recommendations, and Search - serving millions of CNN users via CNN web and mobile apps. The team is also leading the exploration and evaluation of Generative AI for CNN use-cases. Our commitment to using state-of-the-art tools and methods ensures we stay at the forefront of technological innovation.
About the Job/ Responsibilities
As a Sr. Staff Machine Learning Engineer on the CNN Machine Learning & Science Team, you will
- Lead the design, research, modeling, engineering, and evaluation of ML models and systems at CNN.
- Use and build upon open-source Machine Learning models/ projects/ research papers in Natural Language Processing (NLP), Embeddings, Recommendation systems, Ranking systems, and more.
- Lead the exploration, evaluation, prompt-engineering and fine-tuning of Large Language Models (LLMs) for CNN use-cases.
- Proactively counsel cross-functional Engineering and Product leaders in strategic planning and demonstrate good judgment in setting and delivering strategic goals for the team.
- Collaborate with ML Platform engineers and leaders to improve model training, deployment and inference at scale.
- Author, test, review, and optimize production-level code while executing best practices in version control and code integration.
- Mentor and influence engineers across organizations and lead by example with your work.
- Collaborate with data scientists, engineers, product teams, editorial teams and other key stakeholders and drive ML projects from business problem to completion.
- Motivate, inspire and create a culture of experimentation and data-driven innovation while constantly striving to be an advocate for doing what is right for our customers.
The Essentials
- Advanced degree (M.S., or Ph.D.), in computer science, machine learning or related technical fields.
- 8+ years of industry experience, with 6+ years of relevant machine learning experience.
- Experience as a tech lead driving large projects from idea to production while working with a wide set of stakeholders.
- 6+ years of programming experience with Python, Go, Java or similar.
- Experience in Machine Learning, NLP, Recommendation/ Ranking Systems/ Search and applying these techniques at scale.
- Experience with ML packages such as PyTorch, Tensorflow, and Scikit-Learn.
- Experience with SQL and database systems such as Snowflake and DynamoDB
- Experience in the training, evaluation, productionalization, tuning and monitoring of ML solutions at scale.
- Experience designing and running A/B tests at scale.
- Excellent written and verbal communications skills, be comfortable presenting to large audiences
The Nice to Haves
- Experience using Large Language Models such as Mistral or Llama in research and production environments.
- Published research papers on NLP, Recommendation/ Ranking Systems, Search.
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 www.wbd.com/guiding-principles/ 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 the diversity of our society and the world around us. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status 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.
In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery's total compensation package for employees. Pay Range: $159,600.00 - $296,400.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.

Top Skills

Go
Java
Python

What the Team is Saying

Deepak
Nicole
The Company
HQ: New York, NY
40,000 Employees
Hybrid Workplace

What We Do

Warner Bros. Discovery is a premier global media and entertainment company, offering audiences the world’s most differentiated and complete portfolio of content, brands and franchises across television, film, sports, news, streaming and gaming. We're home to the world’s best storytellers, creating world-class products for consumers.​

WBD is bringing together the scripted and the unscripted, the local and the global, the timely and the timeless. Taking the world’s greatest possibilities and making them a reality. Creating impact, inspiring imagination, and building connections. Here you can succeed, here you are supported, here you are celebrated.

Why Work With Us

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.

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Employees engage in a combination of remote and on-site work.

Warner Bros. Discovery offers a combination of hybrid, on-site and remote roles. For more information, please refer to the given job description.

Typical time on-site: Flexible
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