The Role

We are looking for a seasoned Machine Learning Engineer with strong leadership capabilities to join the Connected Services AIML team as a Technical Lead.

You will architect and implement the algorithmic solutions that power our industrial IoT platform, while guiding a team of engineers and scientists to deliver high-impact, production-grade systems — turning large-scale sensor data into intelligence that keeps connected assets running.

What You’ll Do (Impact Areas)

- Architect & deploy ML solutions: design and deploy models for predictive maintenance, anomaly detection, asset optimization, and time-series forecasting using large-scale sensor data from connected devices.
- Build production infrastructure: develop robust data pipelines and real-time inference systems integrated with edge and cloud infrastructure.
- Lead technical execution: own the end-to-end delivery of ML projects, from ideation to deployment.
- Mentor & set the standard: guide a team of ML and software engineers; define and enforce best practices in model development, testing, and deployment.
- Partner cross-functionally: work with product managers and domain experts to align technical solutions with business goals.

What Success Looks Like

- Production-grade models for predictive maintenance and anomaly detection deployed and reliably serving real-time inference at scale.
- Robust, well-documented pipelines moving sensor data from edge to cloud with minimal latency and downtime.
- A high-performing ML and software engineering team operating against clear, enforced best practices.




- Technical roadmaps that map directly to business outcomes and are delivered on time, from ideation to deployment.

Core Competencies

- Technical leadership and end-to-end project ownership in a production environment.
- Strong ML/AI foundations: supervised and unsupervised learning, classification, regression, clustering, and deep learning.
- Production engineering mindset: data pipelines, real-time inference, and edge + cloud deployment.
- Mentorship and the ability to raise the bar across an engineering team.
- Excellent communication and cross-functional collaboration.

What You Bring (Qualifications)

Required

- Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, or a related field.
- 5+ years of experience in machine learning and software engineering.
- Proven experience leading technical teams or projects in a production environment.
- Solid understanding of core ML/AI algorithms: supervised and unsupervised learning, classification, regression, clustering, and deep learning techniques.
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn), SQL, and cloud platforms.
- Experience with time-series data.
- Excellent communication and cross-functional collaboration skills.

Preferred

- Advanced degree in Computer Science, Electrical Engineering, Statistics, or a related field.
- Experience in industrial sectors.
- Knowledge of MLOps tools (MLflow, Airflow, Docker, Kubernetes).
- Experience with one or more of signal processing, edge computing, and physics-informed ML models.

Required Skill Profession

Computer Occupations

📌 Machine Learning Engineer Technical Lead (San Pedro Garza García)
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📍 San Pedro Garza García