Data Science and Machine Learning Engineer
The unified electrical digital twin · Mexico City, Mexico · Hybrid
Weak hiring record · median 63 days open
All reasons
- Open 143 days
- 53% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
ETAP empowers customers to make informed decisions throughout the life cycle of their projects with innovative software solutions for electrical systems. By applying ETAP solutions, customers experience continuous intelligence during design and engineering and into operations and maintenance using a unified electrical digital twin platform. ETAP supports customers in their digital transformation and sustainable energy transitions for a green and smart future, helping them to prioritize safety, maximize reliability, and stay resilient.
Our employees' passion for excellence, innovation, and customer satisfaction is our most-prized resource. If you share that passion — and want to be part of a company that leads the energy transition towards a cleaner and more resilient world for future generations — we invite you to join us!
ETAP is committed to creating a diverse work environment and is proud to be an Equal Opportunity Employer.
Job Title: Data Science & Machine Learning Engineer
Location
On-site (Mexico)
Employment Type
Full-time
About the Role
ETAP’s Cloud Division is expanding its AI/ML capabilities and is seeking a Data Science & Machine Learning Engineer to help design, build, and deploy intelligent systems at scale.
This hybrid role bridges data science and production engineering, focusing not only on building high-performing models but also on operationalizing them in real-world environments. You will work on high-impact initiatives across predictive modeling, graph machine learning, and generative AI, contributing directly to product innovation.
Key Responsibilities
- Design, develop, and deploy machine learning models for classification, regression, ranking, and recommendation systems
- Build end-to-end ML pipelines, from data ingestion and feature engineering to model deployment and monitoring
- Productionize models as scalable APIs using FastAPI, Docker, and cloud platforms (Azure ML)
- Implement robust validation, testing, and monitoring to ensure model performance and reliability in production
- Collaborate with data engineers and software teams to integrate ML solutions into production systems
- Monitor models for drift, retrain pipelines, and continuously improve performance
Required Qualifications
- Strong programming skills in Python, with expertise in Pandas, NumPy, and scikit-learn
- Experience building and deploying end-to-end ML systems in production environments
- Solid knowledge of SQL/NoSQL databases and data pipeline development
- Hands-on experience with XGBoost and/or LightGBM for structured data problems
- Experience with MLOps tools such as Git, Docker, MLflow/Weights & Biases, and Azure ML
- Strong understanding of model evaluation metrics and performance trade-offs
Preferred Qualifications
- Experience with deep learning frameworks (PyTorch or TensorFlow)
- Familiarity with model optimization and tuning (e.g., Optuna)
- Experience with Graph ML (PyTorch Geometric, DGL) or Generative AI (RAG, embeddings, LangChain, LlamaIndex)
- Knowledge of model serialization and deployment standards (ONNX)
- Experience working in cloud-native, distributed environments
What We’re Looking For
- A strong engineering mindset with the ability to take models from concept to production
- Curiosity and passion for applying cutting-edge AI/ML techniques
- A results-driven approach focused on delivering measurable business impact
- Strong collaboration and communication skills across technical and non-technical teams
What We Offer
- Competitive compensation aligned with the Mexican market
- Opportunity to work on cutting-edge AI/ML and cloud technologies
- A collaborative, innovative, and inclusive work environment
- Exposure to global teams and impactful projects
ETAP requires all successful applicants to undergo and pass a comprehensive background check before they start employment. Background checks will be conducted in accordance with local laws and may, subject to those laws, include proof of educational attainment, employment history verification, proof of work authorization, criminal records, identity verification, credit check. Certain positions dealing with sensitive and/or third party personal data may involve additional background check criteria.
ETAP is an Equal Opportunity Employer. We are committed to being an exemplary employer with an inclusive culture, developing a workplace environment where all our employees are treated with dignity and respect. We value diversity and the expertise that people from different backgrounds bring to our business.
Come and join ETAP to create the transformative technology that enables our customers to engineer a better world.
Skills
- Machine Learning
- Generative AI
- FastAPI
- Docker
- Azure ML
- Python
- Pandas
- NumPy
- scikit-learn
- SQL
- XGBoost
- LightGBM
- MLOps
- Git
- MLflow
- Weights & Biases
- Deep Learning
- PyTorch
- TensorFlow
- Retrieval-Augmented Generation
- Embeddings
- LangChain
- LlamaIndex
- ONNX
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