Senior Machine Learning Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Design, develop, and implement advanced ML solutions in high-availability and low-latency production environments.

• Choose suitable algorithms, optimize models, and ensure code quality.

• Create human-readable ML platforms for both humans and agents, featuring modular pipelines, explicit contracts, documented executable semantics, and reproducible environments.

• Define which experiments can be generated and validated automatically, and which decisions necessitate human design or formal verification.

• Set boundaries for high-impact, regulated, or irreversible use cases.

• Lead technical initiatives and high-impact projects across multiple teams and domains.

• Serve as a technical reference and guide key decision-making.

• Establish data strategies, feature selection, preprocessing, and efficient, scalable model architectures.

• Collaborate with product leaders, data scientists, and engineering teams to align developments with strategic objectives.

• Ensure the successful integration and deployment of solutions.

• Evaluate and enhance the ML stack, tools, processes, and MLOps practices.

• Mentor junior and mid-level engineers.

• Promote technical excellence, innovation, and continuous improvement within the team and organization.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related fields.

• Over 5 years of proven experience in applied machine learning, focusing on the design, development, and deployment of models in large-scale production environments.

• Advanced proficiency in Python and its ecosystem of ML libraries.

• Hands-on experience with PyTorch, TensorFlow, Scikit-learn, and XGBoost.

• Solid experience with AWS, GCP, or Azure, including specific services for ML and knowledge of their architectures.

• Demonstrated ability to design and build end-to-end ML solutions.

• In-depth knowledge and practical experience in MLOps, including CI/CD pipelines for ML, model and data versioning, performance monitoring, and rollback strategies.

• Experience leading technical teams, managing ML projects, or directing complex technical initiatives.

• Experience with generative models, NLP, computer vision, or time series (valued).

• Knowledge of data privacy, AI ethics, model interpretability, and model governance (valued).

• Participation in technical communities, open source projects, publications, or speaking engagements (valued).

• Experience with MLflow, Kubeflow, DVC, Airflow, or Vertex AI (valued).

• Utilization of AI agents in real-world ML productive work, with discernment on where they add value and where they introduce systemic risk.

• Strong technical leadership, influence, and mentoring skills.

• Effective and persuasive communication with both technical and non-technical stakeholders.

• Strategic mindset and business-oriented approach.

• Proven ability to make quick decisions and solve complex, ambiguous problems.

🏝️ Benefits

• 100% remote work with hours aligned to CST.

• Unlimited PTO.

• Annual development budget: access to courses, certifications, and conferences.

• Equipment budget.

• Access to private medical coverage or health insurance subsidies.

• Career plan and mentorship with AI and technology experts.

• Dynamic and flexible startup environment.

• Autonomy to make decisions and propose ideas, with a focus on results rather than hours worked.

• Culture prioritizing flexibility and well-being.

• Work-life balance.