Senior Machine Learning Engineer (Industrial AI)

Location: Remote, with Almaty listed as the city/region. Employment under the labor law of the Republic of Kazakhstan.

Company

5 LAB supports a global energy technology customer building digital solutions for reliable and sustainable power generation, transmission, transformation, and energy transition.

What you will do

• Lead end-to-end AI solution delivery from feasibility and data discovery through validation, deployment, and monitoring.
• Integrate operational, maintenance, engineering, asset, and sensor data through reliable pipelines and quality controls.
• Design and evaluate supervised and unsupervised learning, time-series models, deep learning, Generative AI, and RAG solutions.
• Build production-ready AI services with scalable APIs, cloud-native workflows, MLOps, observability, and maintainable deployments.
• Collaborate with domain experts, data owners, IT, cybersecurity, and software teams to deliver measurable outcomes and reusable AI components.
• Mentor engineers and data scientists, conduct reviews, share knowledge, and contribute to patents and publications where relevant.

Requirements

• Master’s degree or PhD in Computer Science, Data Science, Mathematics, Engineering, Physics, or a related quantitative field.
• 7+ years of experience building and deploying ML/AI systems in industrial, infrastructure, energy, or enterprise environments.
• Strong Python and software-engineering skills, including ML and deep-learning frameworks, APIs, testing, containers, and CI/CD.
• Experience with time-series data, anomaly detection or prediction, large imperfect datasets, and robust validation for rare or imbalanced events.
• Hands-on experience deploying ML and Generative AI solutions, including MLOps, cloud or enterprise integration, RAG or agentic patterns, monitoring, and responsible AI practices.
• Sound technical judgment and communication skills, including selecting appropriate methods, collaborating with domain experts, and explaining model behavior and trade-offs.

Nice to have

• Experience with industrial operations, complex machinery, operational reliability, predictive maintenance, or comparable asset-intensive domains.
• Knowledge of advanced time-series and rare-event methods, transfer learning, uncertainty estimation, or cross-site model generalization.
• Knowledge graphs, semantic or vector search, document intelligence, and linking unstructured evidence with structured operational data.
• Cloud AI platforms, model registries, container orchestration, streaming architectures, or delivery of reusable AI platforms.

Culture & Benefits

• Remote work with an international team.
• Monday–Friday schedule, 8 working hours per day.
• Employment under the labor law of the Republic of Kazakhstan.
• Medical insurance compensation after the probationary period.
• Growth opportunities.