As part of the IBM team, your role will primarily focus on applying your expertise in Artificial Intelligence (AI), Machine Learning (ML), and Data Science to develop, deploy, and optimize AI models within production environments. This will involve ensuring that these models are scalable, efficient, and reliable while solving complex challenges across industries.
Responsibilities
- AI/ML Model Development and Deployment. You will lead the development of AI/ML models using advanced techniques such as neural networks, deep learning, and statistical modeling. You will ensure these models are deployed effectively in production environments with a focus on scalability and high performance.
- Hands-On Technical Expertise. With your knowledge of developing large language models (LLMs), you will play an integral role in implementing and optimizing these models in distributed systems. You will have hands-on experience with microservice architecture, REST APIs, and container orchestration platforms like Kubernetes to ensure smooth deployment and operation.
- MLOps and CI/CD Integration. You will collaborate with cross-functional teams to integrate MLOps pipelines with continuous integration/continuous deployment (CI/CD) tools, ensuring that machine learning models are seamlessly integrated into production workflows. This will include working with tools like Jenkins, Travis CI, and GitLab CI.
- Staying Ahead of the Curve. The AI/ML field evolves rapidly, and you’ll be expected to stay updated with the latest advancements in technologies and frameworks. Contributing to the improvement and development of new AI frameworks, libraries, and methodologies will be key to your success.
- Cross-Functional Collaboration. You’ll interact with a diverse set of teams and stakeholders, including non-technical personnel. Your ability to communicate complex technical concepts to non-technical stakeholders will be crucial in ensuring alignment and progress across teams.
- Ensuring Quality and Security. As you design and deploy models, you’ll adhere to industry best practices, ensuring high standards of code quality, performance, security, and compliance with AI engineering standards.
- Performance Optimization. You will work on optimizing AI algorithms for both performance and scalability, ensuring the models can handle vast datasets and respond in real-time to production demands.
Required Technical and Professional Expertise
- Programming Skills. Expertise in Python and C++ is crucial, along with experience in using machine learning libraries like TensorFlow and PyTorch to develop production-grade AI models.
- Data Handling and Integration. Your role will involve working with large datasets, so proficiency in data integration, cleansing, and shaping will be essential. You will also be expected to work with databases, including open-source options like MongoDB, CouchDB, and CockroachDB.
- DevOps Skills. A solid understanding of DevOps principles, including experience with Git, CI/CD pipelines, and containerization tools such as Docker and Kubernetes, is essential. You’ll be responsible for managing AI models in production using these tools.
- Open-Source Contribution. While not mandatory, experience contributing to open-source AI projects or leveraging open-source AI frameworks will be a strong plus, highlighting your commitment to collaborative development and the broader AI community.
- Problem-Solving and Analytical Skills. Strong problem-solving and analytical abilities will be key to overcoming the complex challenges you’ll face in optimizing algorithms and ensuring their scalability.
- AI Compiler/Runtime Expertise. Familiarity with AI compilers and runtime environments is an advantage, helping you fine-tune the performance of machine learning models.
- Agile Methodologies. Experience in Agile development is highly desirable, as you will work in an iterative development process to ensure efficient and timely delivery of AI-based solutions.
Preferred Technical and Professional Expertise
- A proven ability to implement, optimize, and troubleshoot complex machine learning algorithms, neural networks, and statistical models, solving real-world problems with AI.
- Proficiency in working with distributed systems, microservice architectures, and integrating REST APIs to ensure the scalability and efficiency of AI solutions.
- Experience collaborating with cross-functional teams and integrating MLOps pipelines into continuous integration and deployment processes, ensuring seamless workflows for AI/ML models.
- A track record of keeping up with the latest AI/ML advancements and contributing to the growth of AI frameworks, tools, and libraries.
- A proven ability to communicate complex technical concepts in a clear, understandable way to non-technical stakeholders, ensuring alignment and collaboration.
- A commitment to ensuring the highest standards of code quality, security, and compliance in your AI/ML projects.
- Experience with Kubernetes and container orchestration platforms to deploy and manage machine learning models in production environments, ensuring scalability and efficient AI infrastructure management.
About IBM
IBM is an industry leader that has been at the forefront of technological innovation for over a century. We are one of the largest and most trusted technology and consulting employers globally. From pioneering artificial intelligence to exploring the potential of quantum computing and blockchain, IBM continues to push the envelope of what’s possible.
As an IBMer, you will join a diverse community of professionals who share your passion for learning, growth, and making a tangible impact on the world. You will have the opportunity to innovate, experiment, and continuously develop your career. We foster a culture of inclusivity, trust, and responsibility where every individual is empowered to contribute and thrive.
Your Life @ IBM
At IBM, we are committed to creating an environment where everyone can grow, collaborate, and thrive, regardless of their background. We believe in the importance of continuous learning, and our employees are encouraged to stay curious, embrace feedback, and transform themselves along with the company. As part of the IBM family, you will be entrusted with the responsibility to make bold decisions, lead with a can-do attitude, and always focus on driving meaningful outcomes for our customers.