Sr. Principal Data Scientist
Atlanta, GA · On-site
Causal inference, experimentation & uplift modelling * NLP, generative AI & multimodal ML systems * Computer vision & video intelligence pipelines * Apply rigorous statistical thinking ...
Sr. Principal Data Scientist
Atlanta, GA · On-site
Causal inference, experimentation & uplift modelling * NLP, generative AI & multimodal ML systems * Computer vision & video intelligence pipelines * Apply rigorous statistical thinking ...
Sr Data Engineer
$110K - $132K/yr
... ML workloads * Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows * Develop and optimize RAG (Retrieval ...
Sr Data Engineer
$110K - $132K/yr
... ML workloads * Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows * Develop and optimize RAG (Retrieval ...
Sr Data Engineer
Atlanta, GA · On-site
$110K - $132K/yr
... ML workloads * Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows * Develop and optimize RAG (Retrieval ...
Sr Data Engineer
Atlanta, GA · On-site
$110K - $132K/yr
... ML workloads * Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows * Develop and optimize RAG (Retrieval ...
Senior AI Engineer
$100K - $138K/yr
Tune inference performance through KV cache management, paged attention, batching strategies, and ... Build and maintain container images, registries, and CI/CD pipelines for AI/ML services.
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Senior AI Engineer
$100K - $138K/yr
Tune inference performance through KV cache management, paged attention, batching strategies, and ... Build and maintain container images, registries, and CI/CD pipelines for AI/ML services.
Embedded Python Engineer
Atlanta, GA · On-site
$126K - $166K/yr
Deploy and optimize ML models (TFLite, ONNX) for real-time inference on edge hardware, including quantization and pruning workflows * Profile and tune code for memory, latency, and power efficiency ...
Embedded Python Engineer
Atlanta, GA · On-site
$126K - $166K/yr
Deploy and optimize ML models (TFLite, ONNX) for real-time inference on edge hardware, including quantization and pruning workflows * Profile and tune code for memory, latency, and power efficiency ...
The features this framework produces - ML- and LLM-generated alike - power everything from analytics to training to inference to user-facing rendering. What You'll Do * Design and own infrastructure ...
The features this framework produces - ML- and LLM-generated alike - power everything from analytics to training to inference to user-facing rendering. What You'll Do * Design and own infrastructure ...
Staff Software Engineer
Atlanta, GA · On-site
The features this framework produces - ML- and LLM-generated alike - power everything from analytics to training to inference to user-facing rendering. What You'll Do * Design and own infrastructure ...
Staff Software Engineer
Atlanta, GA · On-site
The features this framework produces - ML- and LLM-generated alike - power everything from analytics to training to inference to user-facing rendering. What You'll Do * Design and own infrastructure ...
... ML systems. * Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers. * Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference ...
... ML systems. * Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers. * Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference ...
Machine Learning Lead Engineer
Peachtree Corners, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Peachtree Corners, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Morrow, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Morrow, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Doraville, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Doraville, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Stone Mountain, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Stone Mountain, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Marietta, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Marietta, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Redan, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Redan, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Conley, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Conley, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Dunwoody, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Dunwoody, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Atlanta, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Atlanta, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Fairburn, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Fairburn, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Vinnings, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Vinnings, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Smyrna, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Machine Learning Lead Engineer
Smyrna, GA · On-site
$134K - $224K/yr
Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference * Optimize model performance, scalability, and reliability in production ...
Ml Inference information
What is a $900000 AI job?
A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.
What is ML inference?
ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.
What is the difference between Ml Inference vs Data Scientist?
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research institutions, tech firms, consulting |
ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.
What engineer makes $500,000 a year?
Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.
Which 3 jobs will survive AI?
Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.
What are some common challenges faced by ML Inference Engineers when deploying models to production?
ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.
Will MLE be replaced by AI?
Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.
What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?
To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Georgia? For Ml Inference jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Georgia look for? The top searched job categories for Ml Inference jobs in Georgia are:
What cities in Georgia are hiring for Ml Inference jobs? Cities in Georgia with the most Ml Inference job openings:
Job description
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 a Sr. Principal Data Scientist, you will operate at the highest technical individual-contributor level at Warner Bros. Discovery-serving as a company-wide authority in advanced Data Science, Machine Learning, and Applied AI.
This role is designed for an elite practitioner with 15-18+ years of experience, including 10-14 years of deep, hands-on expertise in Data Science, ML, and AI systems at enterprise scale. Unlike leadership or management roles, this position is purely an IC role, focused on technical depth, architectural rigor, and scientific excellence, without formal people-management responsibilities.
You will design, architect, and deliver some of WBD's most complex and business-critical AI systems, directly influencing how the company creates, distributes, personalizes, monetizes, and optimizes content across streaming, linear TV, advertising, and direct-to-consumer platforms.
This is a hands-on, high-impact role for a technologist who thrives on solving unsolved problems, pushing the boundaries of applied ML, and translating advanced science into durable business advantage.
1. Enterprise-Grade Applied AI & ML Leadership (IC)
- Act as one of WBD'smost senior technical ICsin Data Science and Machine Learning.
- Lead theend-to-end design and implementationof advanced ML systems across:
- Content intelligence & metadata enrichment
- Audience modelling & personalization
- Forecasting, optimization, and experimentation
- Advertising intelligence & monetization analytics
- Settechnical direction and standardsfor complex ML implementations without direct people management.
2. Advanced Modelling & Scientific Excellence
- Design and implementstate-of-the-art models, including:
- Large-scale recommender systems
- Time-series forecasting & probabilistic models
- Causal inference, experimentation & uplift modelling
- NLP, generative AI & multimodal ML systems
- Computer vision & video intelligence pipelines
- Apply rigorous statistical thinking, experimentation discipline, and scientific validation to all solutions.
- Serve as afinal technical reviewerfor high-risk or high-impact ML solutions.
3. Architecture of Scalable ML Systems
- Architectproduction-grade ML systemsintegrated with WBD's cloud data ecosystem (AWS, Snowflake, GCP).
- Define best practices for:
- Feature engineering & feature stores
- Model lifecycle management & MLOps
- CI/CD for ML, model monitoring, and drift detection
- Reproducibility, governance, and responsible AI
- Partner deeply with data engineering, platform, and product engineering teams to ensure scalable, resilient delivery.
4. High-Impact Business Problem Solving
- Own and delivermission-critical AI solutionsacross:
- Content performance prediction & ratings intelligence
- Marketing attribution & lifecycle analytics
- Search, discovery & ranking systems
- Ad load optimization & pricing intelligence
- Operational forecasting & automation
- Translate complex modelling outputs intoclear, executive-ready insightsthat drive decisions.
5. Executive & Cross-Functional Influence (Without Line Management)
- Serve as atrusted technical advisorto senior leaders across Streaming, Content, Ad Sales, Marketing, and Technology.
- Communicate complex ML concepts with clarity and credibility to non-technical stakeholders.
- Influence enterprise AI roadmaps, architectural decisions, and investment priorities through expertise-not hierarchy.
6. Technical Mentorship & Community Leadership
- Mentor senior and staff-level data scientists throughtechnical guidance, design reviews, and deep problem-solving.
- Contribute to internal AI communities of practice, technical forums, and standards bodies.
- Elevate overall engineering and scientific rigor across the Data Science organization.
Qualifications & Experiences:
- Master's or Ph.D.in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, Operations Research, or related disciplines.
- 18-20 yearsof total experience, with13-15 yearsin Data Science/ML, including hands-on technical leadership.
- Deep expertise in:
- Predictive modeling, optimization, and advanced ML techniques
- MLOps and large-scale model deployment
- Modern cloud ecosystems (AWS/GCP/Snowflake)
- Python, PyTorch, TensorFlow, SQL, ML frameworks
- Experiment design, causal inference, and statistical modeling
- Demonstrated experience in Media & Entertainment, streaming, digital advertising, or consumer intelligence.
- Strong track record of delivering enterprise-impact through AI solutions.
- Exceptional communication skills, including the ability to influence executives and inspire technical teams.
Preferred
- Experience developing or customizing Large Language Models or multimodal foundation models.
- Patent, publication, or conference-track record in ML/AI.
- Experience with video intelligence, CV for media workflows, or content metadata systems.
- Experience partnering with product and engineering organizations in a fast-paced environment.
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 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, 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.