Apollo HealthAxis - Machine Learning Engineer - PyTorch/Tensorflow (3-6 yrs)

Role Overview :

We are seeking a highly skilled and motivated Machine Learning Engineer to join our team in Hyderabad. The ideal candidate will have a strong background in deep learning, proficiency in advanced frameworks like PyTorch or TensorFlow, and expertise in medical image processing.

This role involves designing, implementing, and optimizing machine learning models to solve complex challenges, particularly in the medical imaging domain.

Key Responsibilities :

- Model Development : Design and develop deep learning models, including but not limited to Convolutional Neural Networks (CNNs) and Transformer architectures.

- Medical Image Processing : Process and analyze medical imaging data (X-rays, CT scans, MRIs) to extract meaningful insights and patterns.

- Optimization : Optimize machine learning models for performance, scalability, and deployment.

- Data Preprocessing : Clean, preprocess, and augment datasets to improve model accuracy and robustness.

- Collaboration : Work closely with cross-functional teams, including data scientists, software engineers, and domain experts, to define requirements and deliver solutions.

- Research : Stay updated with the latest advancements in deep learning and medical imaging technologies to continuously improve and innovate.

- Deployment : Implement and deploy models into production environments while ensuring scalability and efficiency.

Required Skills and Qualifications :

- Deep Learning Expertise : Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.

- Architectures : In-depth knowledge of CNNs and Transformer architectures.

- Medical Image Processing : Proven expertise in processing and analyzing medical imaging data like X-rays, CT scans, and MRIs.

- Programming Skills : Proficiency in Python and related libraries (NumPy, SciPy, OpenCV, etc.)

- Data Handling : Experience with data preprocessing techniques and working with large-scale datasets.

- Algorithm Design : Strong understanding of machine learning algorithms and optimization techniques.

- Version Control : Familiarity with Git for code versioning and collaboration.

- Deployment Tools : Knowledge of Docker, Kubernetes, or cloud platforms for model deployment.

- Problem-Solving : Excellent analytical and problem-solving skills with a detail-oriented mindset.

Preferred Skills :

- Experience with reinforcement learning or generative models.

- Familiarity with DICOM standards and tools.

- Knowledge of parallel computing and GPU programming (CUDA).

- Background in healthcare or biomedical engineering.

- Experience with MLOps tools and pipelines (MLFlow, Kubeflow, etc.

- Publications in relevant fields or participation in open-source projects