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Director Google Machine Learning Engineer Jobs in Virginia

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly ... Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure ... With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure ... With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure ... With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure ... With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure ... With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure ... With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional ...

Machine Learning Engineer Richmond, Virginia (5 Days Onsite) need local within commute About the ... Direct experience with Azure AI Foundry and Copilot Studio Experience integrating AI agents into ...

Machine Learning Engineer

Arlington, VA ยท On-site

$77K - $176K/yr

R0242757 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

Machine Learning Engineer

Arlington, VA ยท On-site

$77K - $176K/yr

R0242766 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

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Director Google Machine Learning Engineer information

Is L7 senior at Google?

At Google, L7 is considered a senior-level position, typically involving significant technical expertise and leadership responsibilities. It is often associated with senior engineers or managers, depending on the role and team structure.

What engineer makes $500,000 a year?

A senior Google Machine Learning Engineer or Director level in large tech companies can earn $500,000 or more annually, often including base salary, bonuses, and stock options. These roles typically require extensive experience, advanced skills in machine learning and AI, and often involve leadership responsibilities and high-impact projects.

How much does a Google Engineering director make?

A Google Engineering Director typically earns between $200,000 and $300,000 annually, with total compensation including bonuses and stock options often exceeding this range. Compensation varies based on experience, location, and performance, and senior roles may include additional benefits and incentives.

Will MLE be replaced by AI?

As a Google Machine Learning Engineer, the role involves developing and deploying AI models, but AI is a tool that enhances rather than replaces MLE work. MLEs focus on designing, optimizing, and maintaining machine learning systems, which require expertise in data science, programming, and domain knowledge that AI cannot fully replicate. The role is expected to evolve with advancements in AI, emphasizing collaboration with AI systems rather than replacement.
What are the most commonly searched types of Google Machine Learning Engineer jobs in Virginia? The most popular types of Google Machine Learning Engineer jobs in Virginia are:
What job categories do people searching Director Google Machine Learning Engineer jobs in Virginia look for? The top searched job categories for Director Google Machine Learning Engineer jobs in Virginia are:
What cities in Virginia are hiring for Director Google Machine Learning Engineer jobs? Cities in Virginia with the most Director Google Machine Learning Engineer job openings:

Machine Learning Engineer

Full Scope

Reston, VA โ€ข On-site

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Job Title:Machine Learning Engineer
Location:Fort Meade, MD
Required Clearance: TS/SCI w/ Full-Scope Poly
Salary:Competitive
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.
Key Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications:
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.