Information Technology & Software
20 Jun
AI Engineer / MLOps Engineer
We are looking for an AI Engineer / MLOps Engineer to join a successful and growing IT company delivering advanced data, AI, and digital transformation solutions for enterprise clients. This role offers the opportunity to work on end-to-end machine learning projects, from model development and deployment to monitoring and governance, using modern AI and MLOps platforms.
Key Responsibilities
Develop, train, validate, and optimize machine learning models
Prepare, analyze, and transform data for AI/ML use cases
Participate in deploying models to testing, staging, and production environments
Monitor model performance, prediction quality, and operational stability
Contribute to defining processes for model versioning, retraining, and controlled change management
Work with IBM Cloud Pak for Data and/or similar ML and AI platforms
Document models, experiments, results, and operational procedures
Collaborate closely with Data Engineering, Analytics, IT, and business stakeholders
Requirements
Minimum 3 years of experience in AI/ML engineering, Data Science, MLOps, or related roles
Hands-on experience developing, training, and evaluating machine learning models
Strong Python programming skills
Experience with libraries such as scikit-learn, pandas, NumPy, or similar tools
Good understanding of the ML lifecycle, including data preparation, training, validation, deployment, and monitoring
Understanding of MLOps principles and practical implementation
Experience working with structured data and databases
Knowledge of model evaluation metrics and result interpretation
Strong communication skills and ability to collaborate with both technical and business teams
Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, or a related field
Nice to Have
Experience with IBM Cloud Pak for Data
Experience with tools such as Watson Studio, Watson Machine Learning, Watson Pipelines, Watson OpenScale, or similar platforms
Experience with other ML/MLOps platforms such as Azure Machine Learning, AWS SageMaker, Databricks, MLflow, or equivalent solutions
Experience automating ML workflows, deploying models, and managing production ML environments
Experience with model monitoring, drift detection, bias/fairness analysis, and model governance
SQL knowledge and experience with relational databases
Experience with TensorFlow, PyTorch, or other advanced ML/DL frameworks
Experience in industries such as financial services, energy, telecommunications, public sector, or similar enterprise environments
Understanding of Data Governance and Data Catalog concepts
Experience working in cloud or hybrid-cloud environments
Interest in Generative AI, Large Language Models (LLMs), and AI-driven innovation
What We Offer
Opportunity to work on impactful AI, ML, and MLOps projects for large-scale enterprise environments
Exposure to leading AI and data platforms, including IBM's data and AI ecosystem
Participation in building and deploying solutions that support real business processes and decision-making
Collaboration with experienced Data Engineering, Analytics, AI, and Business teams
Professional growth in production-grade machine learning, MLOps, AI platforms, and model governance
Continuous learning and development opportunities in emerging AI technologies
Competitive compensation package aligned with your experience and seniority
Flexible and collaborative work environment focused on innovation and knowledge sharing
If you are passionate about building reliable, scalable, and business-driven AI solutions, we'd love to hear from you.