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Manager Tensor Jobs in Washington (NOW HIRING)

Manager Tensor information

What is the difference between Manager Tensor vs Data Scientist?

AspectManager TensorData Scientist
Required CredentialsBachelor's or Master's in Computer Science, Data Analytics, or related fields; certifications like TensorFlow Developer are commonBachelor's or Master's in Data Science, Statistics, Computer Science; certifications like Certified Data Scientist are common
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in tech or AI-focused companiesAnalyzes data, builds models, reports insights in tech, finance, healthcare industries
Employer & Industry UsageUsed in AI, machine learning, and tech companies for managing TensorFlow projectsUsed across industries for data analysis, predictive modeling, and research

The main difference is that a Manager Tensor oversees AI projects involving TensorFlow, focusing on team management and project delivery, while a Data Scientist primarily analyzes data and builds models. Both roles require technical knowledge, but the Manager Tensor role emphasizes leadership and project management within AI initiatives.

What are the key skills and qualifications needed to thrive as a Manager Tensor, and why are they important?

To thrive as a Manager Tensor (commonly referred to as a TensorFlow Manager or Machine Learning Manager), you need a solid background in machine learning, deep learning frameworks (especially TensorFlow), and experience leading technical teams, typically backed by a relevant degree. Proficiency with TensorFlow, Python, data engineering tools, and cloud platforms, along with certifications in machine learning, are highly valued. Leadership, strong communication, and project management skills help you effectively guide teams and collaborate with stakeholders. These skills ensure successful project delivery, innovation, and alignment with organizational goals in complex AI-driven environments.

What are some common challenges faced by a Manager Tensor when leading AI and machine learning teams?

A Manager Tensor often encounters challenges such as balancing technical leadership with strategic oversight, managing projects that involve complex and evolving technologies, and ensuring effective communication among data scientists, engineers, and stakeholders. Additionally, staying current with rapid advancements in AI frameworks and guiding the team through best practices can be demanding. Collaboration across multidisciplinary teams and aligning projects with business objectives are also key aspects of the role.

What is a Manager Tensor?

A Manager Tensor is typically a managerial position responsible for overseeing teams that develop and implement machine learning models using TensorFlow or similar tensor-based frameworks. This role involves coordinating data science and engineering teams, ensuring project goals align with business objectives, and facilitating the deployment of scalable AI solutions. Additionally, a Manager Tensor may be tasked with mentoring staff, managing resources, and staying updated with the latest advancements in artificial intelligence. The position requires strong leadership, technical expertise in machine learning, and experience with deep learning platforms.
What cities in Washington are hiring for Manager Tensor jobs? Cities in Washington with the most Manager Tensor job openings:

LLMOps Engineer with Security Clearance

The Josef Group Inc.

Chantilly, VA • On-site

Other

Posted 9 days ago


Job description

LLMOps Engineer | Top Secret Clearance required - Chantilly VA Salary to 250K and great benefits! Are you passionate about building and operating production-scale Large Language Model infrastructure? We're looking for an experienced LLMOps Engineer to help deploy, optimize, and scale self-hosted AI platforms. What we're looking for:
✅ Deep understanding of LLM internals (Transformers, tokenization, inference, quantization, fine-tuning)
✅ Hands-on experience with vLLM deployment and production operations
✅ Kubernetes, Docker, GPU clusters, and AWS, Azure, or GCP
✅ Expertise serving open-weight models like Llama, Mistral, and Qwen
✅ Experience with tensor parallelism, continuous batching, PagedAttention, KV-cache optimization, and model quantization (AWQ, GPTQ, FP8)
✅ Strong DevOps background with CI/CD, Infrastructure as Code, observability, monitoring, and incident response
✅ Proven success managing production LLM environments for performance, reliability, scalability, and cost efficiency If you've been responsible for keeping a live, self-hosted LLM platform running at peak performance, we'd love to hear from you. 📩 Contact Debbie at The Josef Group, to learn more about this exciting opportunity.