About the Role
We are looking for an AI/ML Engineer to help design, build, and deploy intelligent solutions that drive business value through data and advanced machine learning technologies.
In this role, you will work across the full machine learning lifecycle, from data preparation and model development to deployment, monitoring, and continuous improvement. You will collaborate with cross-functional teams to create scalable AI solutions that support business objectives and operational excellence.
Key Responsibilities
- Design, train, evaluate, and optimize machine learning and deep learning models.
- Build and maintain scalable data pipelines for data ingestion, transformation, and processing.
- Implement MLOps best practices, including model versioning, deployment automation, monitoring, and retraining workflows.
- Explore and apply modern AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and generative AI solutions.
- Deploy AI models into production environments and ensure reliable integration with existing platforms and applications.
- Monitor model performance and continuously improve accuracy, scalability, and efficiency.
- Collaborate with data engineers, software developers, architects, and business stakeholders to deliver impactful solutions.
- Promote responsible AI practices, ensuring transparency, security, and compliance throughout the development lifecycle.
Requirements
- Proven experience as an AI/ML Engineer, Machine Learning Engineer, Data Scientist, or similar role.
- Strong programming skills in Python.
- Hands-on experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Experience working with large-scale data processing platforms such as Spark, Databricks, or similar technologies.
- Knowledge of MLOps tools and practices, including MLflow, Kubernetes, containerization, and CI/CD pipelines.
- Experience with LLMs, RAG architectures, vector databases, and modern generative AI solutions.
- Ability to develop, deploy, monitor, and maintain production-grade machine learning systems.
- Understanding of software engineering best practices, including testing, code reviews, and version control.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Passion for innovation and continuous learning in the AI/ML domain.
Nice to Have
- Experience integrating AI solutions with enterprise applications and business platforms.
- Familiarity with cloud environments and distributed systems.
- Exposure to agentic AI frameworks and autonomous AI systems.
What We Offer
- Opportunity to work on innovative AI initiatives with real business impact.
- Exposure to modern technologies, large-scale datasets, and production AI environments.
- Collaboration with experienced professionals in an international setting.
- Continuous learning and professional development opportunities.
- Flexible and supportive work environment.
- Challenging projects that encourage innovation, ownership, and growth.