AI Engineer

Category: IT Services

Location:

We are looking for a Machine Learning / AI Engineer to design, develop, and deploy AI systems that solve real-world problems at scale. The ideal candidate combines strong machine learning fundamentals with hands-on production experience, strong engineering skills, and the ability to work independently in an evolving environment.

Your Duties

- Design, develop, and deploy machine learning and AI systems for real-world applications.

- Build and optimize custom AI models for domain-specific tasks.

- Design and maintain data mining, data preprocessing, and data-labeling pipelines.

- Work with large datasets, including feature engineering and data preparation.

- Apply machine learning techniques across areas such as LLMs, NLP, computer vision, or other AI domains.

- Train, evaluate, optimize, and improve machine learning models.

- Develop and maintain model deployment and MLOps pipelines.

- Deploy and serve models using cloud platforms and containerized environments.

- Use tools such as Docker, Git, and relevant MLOps platforms in collaborative development workflows.

- Analyze model performance and identify opportunities for improvement.

- Communicate technical concepts and project progress to non-technical stakeholders.

Requirements

- 2–5 years of hands-on experience building and deploying ML/AI models in production environments.

- Strong proficiency in Python.

- Practical experience with PyTorch and/or TensorFlow.

- Experience designing and architecting custom AI models.

- Experience with LLMs, NLP, computer vision, or other AI domains.

- Strong understanding of supervised and unsupervised learning, deep learning architectures, optimization, and evaluation metrics.

- Experience with data preprocessing, feature engineering, data mining, and data-labeling pipelines.

- Familiarity with MLOps tools and model deployment platforms such as MLflow, Kubeflow, or SageMaker.

- Knowledge of cloud platforms and services used for model training and serving, such as AWS Lambda.

- Experience with Docker and containerized model deployment.

- Familiarity with Git and collaborative software development practices.

- Strong analytical and problem-solving skills.

- Ability to communicate complex technical concepts to non-technical stakeholders.

- Curiosity-driven mindset and comfort working with ambiguity.

Details
Originally posted on Himalayas