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AI Engineer
3 weeks ago
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.
Your Role and Responsibilities
- 7+ years of experience in Data Science with a background in machine learning, deep learning, and natural language processing.
- Robust background in traditional AI methodologies, encompassing both machine learning and deep learning frameworks.
- Familiarity with model serving platforms such as TGIS and vLLM.
- Hands-on experience in transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion) is desirable. Experience in testing AI algorithms and models is advantageous.
- Proficiency in Python, C++, Go, Java, and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality products is essential.
- Proficient in full-stack development, adept at frontend (HTML, CSS, JavaScript) and backend (Django, Flask, Spring Boot). Experience integrating AI tech into full-stack projects is a plus. Skilled in integrating, cleansing, and shaping data, with expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB.
- Proficient in developing optimal data pipeline architectures for AI applications, ensuring adherence to client's SLAs.
- Familiarity with Linux platform and experience in Linux app development is desirable.
- Experienced in DevOps, skilled in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes).
- Experience in Generative Ai would be a huge plus.
- AI compiler/runtime skills would be a huge plus.
- Open-source Contribution is a huge plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks is beneficial.
- Strong problem-solving and analytical skills, with experience in optimizing AI algorithms for performance and scalability.
- Familiar with Agile methodologies, adept at collaborative teamwork. Experience in Agile development of AI-based solutions is advantageous, ensuring efficient project delivery through iterative development processes.
- 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.
- Data Science and Generative AI Experience:
- 7+ years of experience in Data Science and Generative AI.
- Background in machine learning, deep learning, and natural language processing.
- Model Experience:
- Hands-on experience with transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion).
- Desirable experience in testing AI algorithms and models.
- Traditional AI Methodologies:
- Robust background in traditional AI methodologies, including machine learning and deep learning frameworks.
- Familiarity with model serving platforms such as TGIS and vLLM.
- Programming Proficiency:
- Proficiency in Python, C++, Go, Java.
- Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products.
- Full-Stack Development:
- Proficient in full-stack development, including frontend (HTML, CSS, JavaScript) and backend (Django, Flask, Spring Boot).
- Experience integrating AI tech into full-stack projects.
- Data Handling Skills:
- Skilled in integrating, cleansing, and shaping data.
- Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB.
- Data Pipeline Architectures:
- Proficient in developing optimal data pipeline architectures for AI applications.
- Ensuring adherence to client's SLAs.
- 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
- AI/ML and Data Science Proficiency:
- 7+ years of expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency.
- Algorithm Implementation and Optimization:
- Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively.
- Large Language Models (LLMs) Development:
- Hands-on experience in developing and deploying large language models (LLMs) in production environments.
- Proficiency in distributed systems, microservice architecture, and REST APIs.
- MLOps Integration:
- 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.
- Continuous Learning and Contribution:
- 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.
- Effective Communication:
- 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.
- Adherence to Industry Standards:
- 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.
- Container Orchestration:
- 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.
This job requires you to be fully COVID-19 vaccinated prior to your start date and proof of vaccination status will be required before your start date. During the Onboarding process you will be asked to confirm your vaccination status, in case you are unable to get vaccinated for any reason, you can let us know at that stage. Please let us know if you are unable to be vaccinated due to medical or religious reasons. IBM will consider such requests on a case by case basis subject to submission of required proof by the candidate before a stipulated date.
Your a world where technology never stands still, we understand that, dedication to our clients success, innovation that matters, and trust and personal responsibility in all our relationships, lives in what we do as IBMers as we strive to be the catalyst that makes the world work better. Being an IBMer means you'll be able to learn and develop yourself and your career, you'll be encouraged to be courageous and experiment everyday . click apply for full job details
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