Job Description
Introduction
At IBM, work transcends a mere job — it is a calling: To build, design, code, consult, think along with clients, sell, make markets, invent, collaborate. The goal is to do better and attempt what has never been thought possible.
Your Role and Responsibilities
As a Staff AI/MLOps Development Engineer at Apptio, you will:
- Collaborate closely with Engineers, Data Scientists, Product Managers, and Designers.
- Help customers identify new savings opportunities in hybrid cloud environments.
- Design and engineer efficient and resilient MLOps platforms and software products that operate at cloud-scale.
- Engage in design, architecture, and code reviews.
- Foster team collaboration and guide roadmap delivery.
- Lead technical discussions and provide leadership in product development.
Key Responsibilities
- Set the direction and goals for the MLOps platform, focusing on project impact and ML system excellence.
- Escalate complex performance and evaluation issues in online/production systems.
- Develop and deploy AI models using deep learning, neural networks, chatbots.
- Incorporate GenAI models within solutions and ensure production-quality deployment pipelines.
- Gather, synthesize, and prioritize requirements to create effective feature roadmaps.
- Develop MLops frameworks, considering trade-offs between approaches.
- Plan and understand ongoing team work and priorities.
- Collaborate with the product team to align solutions with market and customer needs.
- Lead design and code reviews; improve security, testing, performance, and observability.
- Mentor junior team members.
Preferred Education
- Bachelor's Degree in Computer Science, Engineering, or related fields.
Required Technical and Professional Expertise
- Experience with modern software development methodologies: Agile/Kanban, CI/CD, DevOps.
- Proficiency in programming languages such as Python, Java, Go, Scala, C++, or C#.
- Experience designing and implementing AI/MLOps infrastructure.
- Familiarity with cloud-based platforms and data integration.
- Strong problem-solving and analytical skills.
Additional Skills (Preferred)
- API design and implementation.
- Data governance, security, and privacy expertise.
- Linux-based development environments.
- Customer focus, leadership, and team-building skills.
- Advanced knowledge in Big Data.
This job involves technical expertise, leadership, and innovative problem solving to build scalable AI and MLOps solutions.