ML engineer
About the role
The ML Engineer role involves designing, developing, and deploying advanced machine learning and AI solutions to address business challenges and drive organizational growth. The position works closely with Data Scientists and platform teams to turn prototypes into production-ready models, build automated pipelines, and engineer MLOps infrastructure across AWS, GCP, and Azure environments. Responsibilities include analyzing business requirements, developing and deploying ML models, managing model lifecycle, implementing CI/CD/CT pipelines, and maintaining production-grade code and infrastructure. The role also involves researching new MLOps tools and collaborating in a fast-paced, Agile environment.
Must have
- Bachelor's Degree in IT/ICT, Computer Science, Artificial Intelligence, Data Science, Statistics, Software Engineering, or a related discipline.
- 0 to 2 years of experience in Machine Learning Engineering, MLOps, Data Science, or related roles.
- Good understanding of ML and AI concepts, with hands-on experience in ML model development, including models for tabular data and an understanding of Computer Vision and NLP.
- Proficiency in Python (or at least one programming language) for machine learning and automation tasks.
- Working knowledge of ML frameworks and libraries such as PyTorch, Keras, and scikit-learn.
- Experience operationalizing data science projects (MLOps) using at least one platform such as Amazon SageMaker, Google Cloud Vertex AI, or Azure Machine Learning.
- Experience implementing CI/CD/CT pipelines and working with containerization (Docker, Kubernetes) and version control.
- Familiarity with Agile/Scrum practices, with strong problem-solving, teamwork, and communication skills.
Nice to have
- Experience with cloud platforms (AWS, GCP, or Azure) and exposure to Generative AI or Agentic AI solutions will be an added advantage.
Technologies
- Agentic AI
- Agile
- AWS
- Azure
- CI/CD
- Computer Vision
- Data Science
- Docker
- Feature Engineering
- GCP
- Generative AI
- GitLab
- Keras
- Kubernetes
- Machine Learning
- MLOps
- NLP
- Python
- PyTorch
- SageMaker
- scikit-learn
- Scrum
- Statistics
- Vertex AI
Highlights
The position is suitable for candidates with 0 to 2 years of experience, making it ideal for recent graduates or those early in their ML engineering careers. A Bachelor's degree in a relevant field is required. Exposure to Generative AI or Agentic AI solutions is considered an added advantage.
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