Machine Learning Engineer – English Speaking Research

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IBM is a global leader in technology and innovation, dedicated to solving the world’s most complex challenges through advanced research and groundbreaking solutions. Our Watson AI platform and extensive research labs are at the forefront of artificial intelligence and machine learning, driving progress across industries from healthcare to finance. We foster a culture of curiosity, collaboration, and continuous learning, empowering our employees to make a tangible impact on the future of technology.

Descripción del Trabajo

We are seeking a highly motivated and skilled Machine Learning Engineer to join our innovative research team in Barceloneta, Puerto Rico. This role focuses on developing, deploying, and optimizing cutting-edge machine learning models for various research initiatives. The ideal candidate will possess a strong foundation in machine learning principles, exceptional programming skills, and a passion for pushing the boundaries of AI. You will work within an English-speaking research environment, collaborating with global teams to transform complex data into actionable insights and robust solutions. This is an exciting opportunity to contribute to high-impact projects at one of the world’s leading technology and research companies.

Responsabilidades Clave

• Design, develop, and implement advanced machine learning models and algorithms.
• Collaborate with interdisciplinary research scientists and engineers to define project scope and requirements.
• Perform extensive data analysis, feature engineering, and model evaluation to ensure optimal performance.
• Develop and maintain robust MLOps pipelines for model training, deployment, and monitoring.
• Stay current with the latest advancements in machine learning, artificial intelligence, and relevant research fields.
• Present research findings, methodology, and results to internal teams and potentially external scientific communities.
• Contribute to technical documentation, research papers, and patent applications.
• Optimize models for performance, scalability, and efficiency in production environments.

Habilidades Requeridas

• Strong proficiency in Python programming and related data science libraries (NumPy, Pandas, Scikit-learn).
• Extensive experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning) and their applications.
• Experience with natural language processing (NLP), computer vision, or time series analysis.
• Proficiency in data manipulation, cleaning, and feature engineering techniques.
• Excellent problem-solving skills and a strong analytical mindset.
• Strong English communication skills, both written and verbal, for technical discussions and presentations.
• Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related quantitative field.

Cualificaciones Preferidas

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related discipline.
• Experience with cloud platforms (AWS, Azure, GCP) and their machine learning services.
• Familiarity with containerization technologies (Docker, Kubernetes).
• Demonstrated experience in deploying machine learning models into production environments.
• Publications in top-tier AI/ML conferences or journals.
• Experience with distributed computing frameworks (e.g., Spark).
• Knowledge of software engineering best practices (version control, testing, code reviews).
• Fluency in Spanish is a plus but not required.

Ventajas y Beneficios

• Comprehensive medical, dental, and vision insurance plans.
• Generous paid time off, including vacation, sick leave, and holidays.
• 401(k) retirement savings plan with company matching contributions.
• Opportunities for professional development, continuous learning, and career growth.
• Access to cutting-edge research and technology.
• Employee assistance program and wellness initiatives.
• On-site facilities including fitness centers and cafeterias (where applicable).
• Relocation assistance for eligible candidates.

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