Machine Learning Engineer

hace 8 meses

Guadalajara, México IBM A tiempo completo

Introduction

In this role, you’ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

A career in IBM Consulting embraces long-term relationships and close collaboration with clients across the globe.

You’ll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including IBM Software and Red Hat.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you’ll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

Your Role and Responsibilities

As a ML Engeneer you will develop, maintain, evaluate, and test ML solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs.

Required Technical and Professional Expertise

Proven experience working as a Machine Learning Engineer or Sr. Developer working in Data Science, in a professional setting.
- Strong proficiency in programming languages such as Python (Java optional), as well as experience with machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid mathematical and statistical foundations, with knowledge of algorithms, data structures, and optimization techniques.
- Experience with big data technologies (e.g., Spark, Kafka) and working with large-scale datasets.
- Excellent communication and teamwork skills

Preferred Technical and Professional Expertise

Experience with cloud platforms and services (e.g., AWS, Azure, GCP) is a plus.
- Familiarity with renewable energy, power systems, or utilities industry is a plus

About Business UnitIBM Consulting is IBM’s consulting and global professional services business, with market leading capabilities in business and technology transformation. With deep expertise in many industries, we offer strategy, experience, technology, and operations services to many of the most innovative and valuable companies in the world. Our people are focused on accelerating our clients’ businesses through the power of collaboration. We believe in the power of technology responsibly used to help people, partners and the planet.

Being an IBMer means you’ll be able to learn and develop yourself and your career, you’ll be encouraged to be courageous and experiment everyday, all whilst having continuous trust and support in an environment where everyone can thrive whatever their personal or professional background.

Our IBMers are growth minded, always staying curious, open to feedback and learning new information and skills to constantly transform themselves and our company. They are trusted to provide on-going feedback to help other IBMers grow, as well as collaborate with colleagues keeping in mind a team focused approach to include different perspectives to drive exceptional outcomes for our customers. The courage our IBMers have to make critical decisions everyday is essential to IBM becoming the catalyst for progress, always embracing challenges with resources they have to hand, a can-do attitude and always striving for an outcome focused approach within everything that they do.

Are you ready to be an IBMer?

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