53 Senior Data Scientist Media Entertainment jobs in Arlington

At GXO, we're constantly looking for talented individuals at all levels who can deliver the caliber of service our company requires. You know that a positive work environment creates happy employees, which boosts productivity and dedication. On our team, you'll have the support to excel at work and the resources to build a career you can be proud of.

We're out to transform transportation logistics through technology, and our multimillion-dollar commitment to IT underscores its importance to our vision. As a Machine Learning Engineer, you will be responsible for designing, building, and maintaining scalable machine learning systems. You will work closely with data scientists, software engineers, and business stakeholders to deploy models into production, ensure system reliability, and optimize performance across GXO's operations.

Pay, benefits and more.

We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and more.

What you'll do on a typical day:

• Deploy and monitor ML models in production | Use tools like Docker, Kubernetes, and MLflow to ensure scalable and reliable deployment
• Build and maintain data pipelines | Use tools like Airflow, Spark, or Kafka to support model training and inference
• Integrate ML models into business applications | Collaborate with software engineers to embed models into operational systems
• Monitor model performance and data drift | Implement alerting and retraining pipelines
• Clean and preprocess data | Ensure data quality and consistency for modeling
• Work with cross-functional teams | Translate business needs into technical solutions
• Maintain technical documentation | Ensure reproducibility and knowledge sharing
• Optimize ML workflows | Identify and implement improvements in performance and scalability

At a minimum, you'll need:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics or another analytics-related field, or equivalent related work or military experience
• 3-5 years in AI/ML engineering or Data Science, or software engineering with ML focus
• ML Engineering Expertise: Strong understanding of ML lifecycle, from training to deployment and monitoring.
• Programming Proficiency: Advanced Python skills; experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• MLOps Tools: Proficiency in Docker, Kubernetes, MLflow, and CI/CD pipelines.
• Data Engineering: Experience with data pipeline tools (Airflow, Spark, Kafka).
• Cloud Platforms: Familiarity with AWS, GCP , or Azure.

• Collaboration: Ability to work with data scientists, developers, and business stakeholders.
• Communication: Ability to explain GenAI concepts to technical and non-technical stakeholders.

GXO is a leading provider of cutting-edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team - energetic, innovative people of all experience levels and talents who make GXO a great place to work.

We are proud to be an Equal Opportunity/Affirmative Action employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status.

GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers.

All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test.

The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed. Review GXO's candidate privacy statement here.

Job Description Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you’ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming like Python, Scala, or Java. Basic Qualifications: Bachelor’s degree At least 8 years of experience designing and building data-intensive solutions using distributed computing ( experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Plano, TX: $204,900 - $233,800 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to and in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including , childbirth or related medical conditions), , , , , , , genetic information, marital status, , , reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). #J-18808-Ljbffr

Senior Lead Machine Learning Engineer - Garage

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

About the team:

As part of FS AI labs you will be working on AI initiatives within Financial Services with a focus on Applied AI and Machine Learning (AI/ML), Generative AI, Natural Language Processing (NLP), and Responsible AI. The primary objective of FS AI Labs is to drive the research and delivery of innovative AI and ML use cases that leverage these cutting-edge technologies. You will work on exploring new frontiers, build prototypes, and deliver transformative AI use cases that drive Capital One Financial Services business growth and enhance customer experience.

What you’ll do in the role:

• The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.

• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).

• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.

• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.

• Retrain, maintain, and monitor models in production.

• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

• Construct optimized data pipelines to feed ML models.

• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.

• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

• Use programming languages like Python, Scala, or Java.

Basic Qualifications:

• Bachelor’s degree

• At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)

• At least 4 years of experience programming with Python, Scala, or Java

• At least 3 years of experience building, scaling, and optimizing ML systems

• At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications:

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field

• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

• 3+ years of experience developing performant, resilient, and maintainable code

• 3+ years of experience with data gathering and preparation for ML models

• 3+ years of people management experience

• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

• 3+ years of experience building production-ready data pipelines that feed ML models

• Ability to communicate complex technical concepts clearly to a variety of audiences

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description Senior Lead Machine Learning Engineer - Garage As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. About the team: As part of FS AI labs you will be working on AI initiatives within Financial Services with a focus on Applied AI and Machine Learning (AI/ML), Generative AI, Natural Processing (NLP), and Responsible AI. The primary objective of FS AI Labs is to drive the research and delivery of innovative AI and ML use cases that leverage these cutting-edge technologies. You will work on exploring new frontiers, build prototypes, and deliver transformative AI use cases that drive Capital One Financial Services business growth and enhance customer experience. What you’ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming like Python, Scala, or Java. Basic Qualifications: Bachelor’s degree At least 8 years of experience designing and building data-intensive solutions using distributed computing ( experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Plano, TX: $204,900 - $233,800 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to and in the workplace. All qualified applicants will receive consideration for employment without regard to (including , childbirth or related medical conditions), , , , , , , genetic information, marital status, , , reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). #J-18808-Ljbffr

• Lead and conduct cutting-edge research in AI/ML, focusing on areas such as deep learning, natural language processing, computer vision, and reinforcement learning.
• Develop novel AI/ML algorithms, architectures, and methodologies to solve challenging scientific and engineering problems.
• Design and implement machine learning models, train them on large datasets, and evaluate their performance.
• Stay abreast of the latest advancements in AI/ML research and identify opportunities for innovation and application.
• Publish research findings in top-tier peer-reviewed journals and present at leading international conferences.
• Collaborate with cross-functional teams of scientists, engineers, and domain experts to translate research concepts into practical solutions.
• Mentor junior researchers and contribute to the growth of the AI/ML research community within the organization.
• Develop and manage research project roadmaps, ensuring alignment with strategic objectives.
• Secure research funding through grant proposals and collaborative projects.
• Contribute to the intellectual property portfolio through invention disclosures and patent applications.
• Ensure ethical considerations and best practices are integrated into all AI/ML development processes.
• Evaluate and implement new tools and technologies to enhance research capabilities.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Electrical Engineering, or a closely related quantitative field.
• 10+ years of relevant research experience post-Master's or Ph.D., with a significant focus on AI and Machine Learning.
• Exceptional track record of publications in top AI/ML venues (e.g., NeurIPS, ICML, CVPR, ACL) and a strong research reputation.
• Deep theoretical and practical understanding of various machine learning techniques, including supervised, unsupervised, and reinforcement learning.
• Expertise in programming languages commonly used in AI/ML, such as Python, and libraries like TensorFlow, PyTorch, Scikit-learn.
• Experience with large-scale data processing and distributed computing frameworks (e.g., Spark).
• Proven ability to lead research projects from ideation to completion.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.
• Experience with cloud platforms (AWS, Azure, GCP) for AI/ML development is a plus.
• Demonstrated ability to work independently and collaboratively in a research-intensive environment.