{"id":59883,"url":"https://alion.io/job/etap-data-science-and-machine-learning-engineer","title":"Data Science and Machine Learning Engineer","company":{"id":20126,"name":"ETAP","domain":"etap.com","url":"https://alion.io/company/etap","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":9,"ghost_share":0,"stale_share":0.778,"repost_share":0,"time_to_fill_p50_days":56,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Mexico City, Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Digital Twin","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Git","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Weights & Biases","optional":false},{"name":"XGBoost","optional":false},{"name":"DGL","optional":true},{"name":"Edge AI","optional":true},{"name":"Embeddings","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"ONNX","optional":true},{"name":"Optuna","optional":true},{"name":"PyTorch","optional":true},{"name":"RAG","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-06-12T00:00:00Z","employer_posted_date":"2026-06-12","last_verified_at":"2026-10-16T16:23:07Z","board_verified":true,"closed_at":null,"days_open":126,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":126},"description":"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.\nOur 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!\nETAP is committed to creating a diverse work environment and is proud to be an Equal Opportunity Employer.\nJob Title: Data Science & Machine Learning Engineer\nLocation: On-site (Mexico)\nEmployment Type: Full-time\nAbout the Role\nETAP’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.\nThis 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.\nKey Responsibilities\nDesign, develop, and deploy machine learning models for classification, regression, ranking, and recommendation systems\nBuild end-to-end ML pipelines, from data ingestion and feature engineering to model deployment and monitoring\nProductionize models as scalable APIs using FastAPI, Docker, and cloud platforms (Azure ML)\nImplement robust validation, testing, and monitoring to ensure model performance and reliability in production\nCollaborate with data engineers and software teams to integrate ML solutions into production systems\nMonitor models for drift, retrain pipelines, and continuously improve performance\nRequired Qualifications\nStrong programming skills in Python, with expertise in Pandas, NumPy, and scikit-learn\nExperience building and deploying end-to-end ML systems in production environments\nSolid knowledge of SQL/NoSQL databases and data pipeline development\nHands-on experience with XGBoost and/or LightGBM for structured data problems\nExperience with MLOps tools such as Git, Docker, MLflow/Weights & Biases, and Azure ML\nStrong understanding of model evaluation metrics and performance trade-offs\nPreferred Qualifications\nExperience with deep learning frameworks (PyTorch or TensorFlow)\nFamiliarity with model optimization and tuning (e.g., Optuna)\nExperience with Graph ML (PyTorch Geometric, DGL) or Generative AI (RAG, embeddings, LangChain, LlamaIndex)\nKnowledge of model serialization and deployment standards (ONNX)\nExperience working in cloud-native, distributed environments\nWhat We’re Looking For\nA strong engineering mindset with the ability to take models from concept to production\nCuriosity and passion for applying cutting-edge AI/ML techniques\nA results-driven approach focused on delivering measurable business impact\nStrong collaboration and communication skills across technical and non-technical teams\nWhat We Offer\nCompetitive compensation aligned with the Mexican market\nOpportunity to work on cutting-edge AI/ML and cloud technologies\nA collaborative, innovative, and inclusive work environment\nExposure to global teams and impactful projects\nETAP 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.\nETAP 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. 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