AI/ML Engineer

Role Overview :

As an AI/ML Engineer, you will be at the forefront of developing and deploying cutting-edge AI solutions. Your day-to-day will involve designing, building, and training machine learning models, as well as integrating them into production systems. You'll collaborate closely with data scientists, software engineers, and product managers to translate business requirements into impactful AI-driven features. Your work will directly impact our users by enhancing product functionality, improving decision-making, and driving business growth through innovative AI applications.

Key Responsibilities :

- Design and implement scalable machine learning models using Python, PyTorch, and TensorFlow to address complex business challenges.

- Develop and maintain robust data pipelines for efficient data ingestion, processing, and feature engineering to ensure high-quality data for model training.

- Deploy and monitor machine learning models in cloud environments (e.g., AWS, Azure, GCP) using Docker and Kubernetes to ensure reliable and performant AI services.

- Collaborate with cross-functional teams to integrate AI solutions into existing products and workflows, enhancing user experience and driving business value.

- Research and experiment with new AI/ML techniques, including Generative AI, to identify opportunities for innovation and improvement in our AI capabilities.

- Optimize model performance and resource utilization through techniques like model compression, quantization, and distributed training to achieve efficient and cost-effective AI deployments.

Required Skillset :

- Demonstrated ability to design, develop, and deploy machine learning models using Python and deep learning frameworks like PyTorch and TensorFlow.

- Proven experience in building and managing data pipelines for machine learning, including data ingestion, cleaning, and feature engineering.

- Solid understanding of cloud computing platforms (e.g., AWS, Azure, GCP) and experience deploying applications using Docker and Kubernetes.

- Strong knowledge of machine learning algorithms, statistical modeling, and evaluation metrics.

- Excellent communication and collaboration skills to effectively work with cross-functional teams and stakeholders.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.

- Ability to adapt to a dynamic and fast-paced environment, working both independently and as part of a team.

- 3-12 years of relevant experience.