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Mlops Machine Learning Engineer Jobs in Tennessee

... MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage ... machine learning models and large language models. • Conduct research to provide technical ...

... MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage ... machine learning models and large language models. • Conduct research to provide technical ...

Design, develop, and deploy machine learning and deep learning models * Analyze large datasets to ... Familiarity with MLOps tools and frameworks Preferred Qualifications: * Experience with Generative ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Mlops Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Tennessee? For Mlops Machine Learning Engineer jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Mlops Machine Learning Engineer jobs? Cities in Tennessee with the most Mlops Machine Learning Engineer job openings:
Machine Learning Engineer New Grad 2024-2025 -Remote

Machine Learning Engineer New Grad 2024-2025 -Remote

Quora

Jackson, TN • Remote

$139.98K - $168.19K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 7 days ago


Job description

About Quora:

Quora’s mission is to grow and share the world’s knowledge. To do so, we have two knowledge sharing products:

  • Quora: a global knowledge sharing platform with over 400M monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.
  • Poe: a platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including o3, o4-mini, Claude 3.7 Sonnet, GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models.

Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.

This role will be working on our Poe product.

About the Team and Role:

Our small engineering team works on challenging problems every day. We have a culture that's rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. Our engineers focus on creating polished products and writing high quality code by designing APIs and abstractions that are extensible and maintainable. Everyone on the engineering team has a huge impact on our product and our company.

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to uncover new opportunities to the Poe product. You will also play a key role in developing tools and abstractions that our other developers would build on top of.

Responsibilities:
  • Improve our existing Machine Learning systems using your expertise
  • Identify new opportunities to apply Machine Learning to different parts of the Poe product
  • Work with other engineers to implement algorithms and systems in an efficient way
  • Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and training, to realtime LLM application at scale
Minimum Requirements:
  • Ability to be available for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)
  • A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field
  • Strong understanding of mathematical foundations of Machine Learning algorithms
  • Experience of transformer models and LLM applications
  • Strong knowledge of Python or C++, or the ability to learn them quickly
  • A passion for learning and always improving yourself and the team around you
Preferred Requirements:
  • Previous software engineering experience via an internship, work experience, or coding competition
  • Previous industry experience working on natural language processing, language modeling, etc.
  • Passion for Quora's mission and goals

At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.

Additional Information:

We are accepting applications on an ongoing basis.

Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary. For more information on benefits, visit this link: https://www.careers.quora.com/benefits

There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.

  • US candidates only: For US based applicants, the salary range is $107,660 - $161,700 USD + equity + benefits.
  • Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $139,979 - $168,193 CAD + equity + benefits. For all other locations in Canada, the salary range is $130,647 - $156,980 CAD + equity + benefits.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Job Applicant Privacy Notice: https://www.careers.quora.com/applicant-privacy-notice

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