
Data Scientist & AI ELH - RTP 2027
RESEARCH TRIANGLE PARK, NCJobSeen 2w agoSeen in employer's feed 5 days ago
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Job overview
IBM seeks an early‑career professional to join its AI and Data Science team in Research Triangle Park. The Junior Developer will design, develop, and implement AI solutions, collect and clean data, and build predictive models while collaborating with senior developers in an innovative environment.
Skills & qualifications
Skills
Full job description
Introduction
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
We are seeking a motivated and technically skilled early-career professional to join our AI and Data Science development team. As a Junior Developer, you will contribute to the design, development, and implementation of AI solutions and look for ways to efficiently collect, clean, analyze, and visualize data to support business decisions that support real-world applications across enterprise systems. This role is ideal for someone with a strong foundation in machine learning and software engineering who is eager to grow in a collaborative, innovation-driven environment. You will work with Senior Developers to build models helping to create predictive models, generate insights and help optimize company performance
Required technical and professional expertise
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Proficiency in Python and experience with libraries such as NumPy, pandas, scikit-learn.
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Solid understanding of machine learning algorithms and model evaluation techniques.
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Experience with Git and collaborative development workflows.
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Ability to work with structured and unstructured data, including preprocessing and transformation.
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Familiarity with software engineering principles and debugging practices.
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Strong analytical and problem-solving skills.
Preferred technical and professional experience
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Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
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Exposure to model deployment using Docker, REST APIs, or cloud platforms (AWS, Azure, GCP).
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Understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD pipelines).
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Knowledge of distributed systems, storage architectures (e.g., IBM Storage Scale), and performance optimization.
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Familiarity with Linux environments and container orchestration (e.g., Kubernetes, OpenShift).
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Awareness of ethical AI principles, including fairness, transparency, and bias mitigation.
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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