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- Openings
- 1
- Posted
- 50 minutes ago
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Job description
About the Role
We are looking for an experienced Machine Learning Engineer to join a rapidly expanding tech company focused on enhancing and scaling machine learning capabilities within its products and platforms. This role offers a chance to work at the intersection of machine learning, software engineering, and cloud infrastructure, moving ML solutions from prototype stages to robust and scalable production deployments.
Key Responsibilities
- Design, develop, and deploy machine learning models and services collaboratively with data scientists, software developers, and product teams to embed ML functionality into technology products.
- Construct and manage MLOps infrastructure and automated pipelines encompassing model training, evaluation, deployment, monitoring, and retraining processes.
- Implement continuous integration and continuous delivery (CI/CD) practices specifically tailored for machine learning workflows to enhance model reliability and performance.
- Develop scalable infrastructure solutions to support production ML models and contribute to ML platform architecture, model serving, observability, and automation ensuring scalability, security, and efficiency of machine learning systems.
Required Qualifications and Skills
- Proven experience in machine learning engineering with solid foundations in software engineering principles.
- Hands-on experience deploying and maintaining machine learning models in production environments.
- Strong proficiency in Python programming language.
- Experience with machine learning libraries such as PyTorch, TensorFlow, or equivalent frameworks.
- Practical knowledge of MLOps technologies including model deployment tools, CI/CD pipelines, experiment tracking, containerization, and automated training and inference workflows.
- Familiarity with container technologies like Docker and orchestration platforms such as Kubernetes.
- Experience working with cloud service providers (AWS, Azure, or Google Cloud Platform).
- Experience with MLOps platforms like MLflow, Kubeflow, or similar is a significant advantage.
- Experience developing scalable APIs and model serving infrastructure is beneficial.
How to Apply
Interested candidates are requested to submit their resumes referencing this job title. Due to the anticipated number of applications, only candidates shortlisted for the role will be contacted.