AI/ML Scientist

Our requirements

• Bachelor’s or advanced degree in Data Science, Statistics, Computer Science, Engineering, Applied Mathematics, Operations Research, or related field.
• Strong proficiency in Python, including experience with scientific and machine learning libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, SciPy, Matplotlib, and related tools.
• Solid understanding of machine learning and statistical modeling concepts, including time-series analysis, feature engineering, optimization, experimentation, and model evaluation techniques.
• Experience applying advanced analytics, AI, and machine learning techniques within mining and metals, energy, infrastructure, manufacturing, or other asset-intensive industrial sectors. Experience with computer vision, Vision AI, and LLM/LVM applications is considered a strong asset.
• Experience working with industrial-scale datasets, including process historian data, sensor data, operational datasets, and time-series data.
• Working knowledge of data engineering and MLOps concepts, including SQL, APIs, ETL/ELT workflows, cloud platforms (Azure, AWS, or GCP), and model deployment practices.
• Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams and rapidly learn and apply new technologies and concepts.
• Ability to frame ambiguous business challenges into structured analytical approaches, and communicate complex technical findings effectively to technical and non-technical audiences.
• The following experience and skills are considered strong assets:
• Familiarity with industrial IT/OT environments, including data historians (e.g., AVEVA PI System), real-time data integration, control systems, instrumentation, P&IDs, and industrial cybersecurity considerations.
• Experience with mathematical optimization techniques and tools, such as CPLEX, Gurobi, FICO Xpress, or similar optimization frameworks.
• Experience operationalizing AI/ML solutions using modern data platforms and MLOps practices (e.g., Databricks, MLflow, CI/CD pipelines, model monitoring, and lifecycle management).
• English level C1

Optional

• Spanish language

Your responsibilities

• Model Development and Deployment:
• Design, develop, validate, and deploy AI/ML models for industrial applications, including predictive maintenance, process optimization, anomaly detection, forecasting, computer vision, and prescriptive analytics.
• Apply advanced AI and machine learning methodologies, including supervised and unsupervised learning, deep learning, reinforcement learning, optimization techniques, and large language models (LLMs), where appropriate, to solve complex industrial challenges.
• Develop robust data pipelines, feature engineering workflows, and analytical frameworks to transform raw operational and process data into actionable insights and production-ready solutions.
• Translate complex analytical findings into practical recommendations aligned with operational goals and business objectives.
• Collaborate closely with process engineers, data engineers, control specialists, and IT/OT teams to deploy AI and machine learning solutions into production environments and integrate models with enterprise systems, operational platforms, dashboards, and decision-support tools.
• Delivery Excellence and Technology Development:
• Partner with clients and internal teams to identify high-value AI opportunities and quantify business impact and value potential.
• Conduct data-driven opportunity assessments, proof-of-value (PoV) studies, and rapid prototyping initiatives to demonstrate measurable business outcomes and communicate insights effectively to internal and external stakeholders.
• Support the end-to-end AI lifecycle, from problem definition and data exploration through model development, validation, deployment, monitoring, and continuous improvement.
• Contribute to the growth of Hatch’s AI and advanced analytics capabilities through the development of reusable frameworks, accelerators, methodologies, and best practices.
• Stay current with emerging trends and technologies in artificial intelligence, machine learning, optimization, and industrial analytics, bringing innovative approaches to client challenges.
• Contribute to technical publications, conference presentations, white papers, and internal knowledge-sharing initiatives.

What we offer

• Flexible work environment
• Long term career development
• Think globally, work locally

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of professional training & courses
• life insurance
• flexible working time
• fruits