We are hiring Sr. Artificial Intelligence / Machine Learning Engineer, who will be responsible for designing and developing machine learning systems, implementing appropriate ML algorithms, and conducting experiments. The candidate must possess strong programming skills, knowledge of data science.

Experience: 5 years

Qualification

• Bachelor’s/Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.

Skill Required:

• Strong experience with object-oriented/object function scripting languages: Python,  C++, Scala, R or Java etc.
• Solid understanding of machine learning algorithms, deep learning, neural networks, and natural language processing.
• Excellent communication skills.
• 5+ years experience developing and deploying machine learning systems into production.
• Strong experience working with a variety of relational SQL and NoSQL databases.
• Experience with at least one cloud provider solution (AWS, GCP, Azure) and their AI/ML services.
• Experience using one of the frameworks / Libraries– Tensorflow, Keras, pytorch, Scikit-Learn etc.
• Experiences with computer vision project using image classification, object detection, image segmentation, and image mask.
• Research, design, and implement machine learning algorithms and models.
• Hands-on experience in unsupervised machine learning techniques and algorithms, such as various clustering algorithms, and dimensionality reduction techniques.
• Industry experience building innovative end-to-end Machine Learning systems.
• Ability to quickly prototype ideas and solve complex problems by adapting creative approaches.
• Experience working with distributed systems, service-oriented architectures, and designing APIs.
• Strong knowledge of data pipeline and workflow management tools.
• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation.
• Experience with big data tools: Hadoop, Spark, Kafka, etc will be big plus.
• Knowledge of DevOps practices for ML model deployment and experience with Docker and Kubernetes is a big plus.