Machine Learning Product Engineer

• Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field.
• 3+ years of hands-on experience in Machine Learning and Python programming.
• Experience with containerization using Docker.
• Experience with containerization using Docker.
• Proven experience deploying ML models in production environments.
• Experience with cloud platforms (AWS, Azure, GCP) for deploying, scaling, and monitoring ML models.

• Collaborate with software engineers, business analysts, and product owners to refine requirements and deliver efficient ML solutions.

• Research, prototype, and deploy ML models with a focus on production-ready solutions.

• Build and maintain data pipelines and features (batch or streaming).

• Debug issues such as data drift, model degradation, latency, and performance bottlenecks.

• Develop scalable Python-based microservices using modular programming practices.

• Apply computer vision and NLP architectures to solve real-world problems.

• Utilize libraries and tools such as OpenCV, PIL, NLTK, HuggingFace, LangChain, Transformers, and VLLM for vision and language tasks.

• Train, fine-tune, and deploy deep learning models using TensorFlow or PyTorch.

• Analyze and visualize model results using Scikit-learn, NumPy, Pandas, Matplotlib, Seaborn, Gradio, Streamlit, or similar tools.

We are looking for a Machine Learning Product Engineer to join our team and play a key role in developing and deploying cutting-edge ML models. The ideal candidate is passionate about AI/ML and has experience building and deploying models in production environments. You will work with complex data, collaborate with cross-functional teams, and leverage ML and deep learning frameworks to deliver impactful solutions.