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AI Engineer

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IBM

1mo ago

  • Job
    Full-time
    Senior Level
  • Data
    IT & Cybersecurity

AI generated summary

  • You must be proficient in Python and C++, experienced with ML libraries, databases, DevOps, Agile, and AI algorithms, with strong problem-solving and communication skills.
  • You will develop and deploy scalable AI models, optimize algorithms, collaborate on MLOps integration, ensure code quality, and communicate technical concepts to stakeholders.

Requirements

  • Required Technical and Professional Expertise
  • Programming Proficiency:
  • Proficiency in Python, C++.
  • Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products.
  • Data Handling Skills:
  • Skilled in integrating, cleansing, and shaping data.
  • Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB.
  • DevOps Experience:
  • Experienced in DevOps practices.
  • Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes).
  • Open-Source Contribution:
  • Open-source Contribution is a plus.
  • Experience in contributing to open-source AI projects or utilizing open-source AI frameworks.
  • Problem-Solving Skills:
  • Strong problem-solving and analytical skills.
  • Experience in optimizing AI algorithms for performance and scalability.
  • AI Compiler/Runtime Skills:
  • AI compiler/runtime skills would be a plus.
  • Agile Methodologies:
  • Familiarity with Agile methodologies.
  • Experience in Agile development of AI-based solutions.
  • Ensuring efficient project delivery through iterative development processes
  • Preferred Technical And Professional Expertise
  • Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively.
  • Proficiency in distributed systems, microservice architecture, and REST APIs
  • Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows.
  • Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies.
  • Proven ability to contribute to the development and improvement of AI frameworks and libraries.
  • Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders.
  • Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams.
  • Proven track record of ensuring compliance with industry best practices and standards in AI engineering.
  • Maintained high standards of code quality, performance, and security in AI projects.
  • Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.

Responsibilities

  • Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency.
  • Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems.
  • Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs.
  • Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment.
  • Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries.
  • Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills.
  • Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security.
  • Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments.

FAQs

What is the role of an AI Engineer at IBM?

The AI Engineer at IBM is responsible for developing and deploying AI models in production environments, optimizing machine learning algorithms, and collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools.

What programming languages should I be proficient in for this role?

Proficiency in Python and C++ is required for this role.

What machine learning libraries are important for this position?

Experience with relevant machine learning libraries such as TensorFlow and PyTorch is essential for developing production-grade AI solutions.

Do I need experience in DevOps practices?

Yes, experience in DevOps practices, including skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes) is required.

Is knowledge of container orchestration important for this role?

Yes, experience using container orchestration platforms like Kubernetes to deploy and manage machine learning models in production environments is important.

Will I need to communicate with non-technical stakeholders?

Yes, strong communication skills are required to effectively convey technical concepts to non-technical stakeholders.

Is it necessary to stay updated with advancements in AI/ML technologies?

Yes, a commitment to staying updated with the latest advancements in AI/ML technologies is expected.

Do I need experience with open-source contributions?

While not mandatory, experience contributing to open-source AI projects or utilizing open-source AI frameworks is considered a plus.

What kind of problem-solving skills are required?

Candidates should possess strong problem-solving and analytical skills, particularly in optimizing AI algorithms for performance and scalability.

Are Agile methodologies relevant to this position?

Yes, familiarity with Agile methodologies and experience in Agile development of AI-based solutions is beneficial.

What personal qualities does IBM value in its employees?

IBM values growth-minded individuals who are curious, open to feedback, collaborative, and willing to engage in courageous decision-making.

Is there support for training and development?

Yes, IBM encourages continuous learning and development, providing opportunities for employees to enhance their skills and career growth.

Does IBM promote diversity and inclusion?

Yes, IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer, welcoming applicants from various backgrounds.

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IBM

Technology
Industry
10,001+
Employees
1911
Founded Year

Mission & Purpose

At IBM, we do more than work. We create. We create as technologists, developers, and engineers. We create with our partners. We create with our competitors. If you're searching for ways to make the world work better through technology and infrastructure, software and consulting, then we want to work with you. We're here to help every creator turn their "what if" into what is. Let's create something that will change everything