IBM recruitment 2023 for freshers | AI Engineer

2023-10-29 Click here to join our placement whatsapp group

An AI Engineer at IBM is not just a job title – it’s a mindset. You’ll leverage the watsonx platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients.
Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive.
Day-to-Day Duties:

Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations.
Documentation and Knowledge Sharing: Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members.
Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation.
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Required Technical and Professional Expertise

Education: Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field.
Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus.
Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI.
Growth mindset: Demonstrate a growth mindset to understand clients’ business processes and challenges.

Preferred Technical and Professional Expertise

Experience: Proven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms.

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