AI/ML Developer

Design and develop platform solution based on best practices and web standards.

Participate in all aspects of product development, from requirements analysis to product release.

Lead features and participate in architecture and design reviews.

Design enterprise platform using agile methodology. This includes creating detailed design using UML, process flows, sequence diagrams, and pseudo-code level details ensuring solution alignment.

You have strong diagnostics, debugging, and troubleshooting skills.

Ability to work flexible hours and stay up to date with competing technologies and passionate about adapting technology to provide business-benefiting solutions balancing with platform limitations.

Provides complete documentation in the form of commented code, problem status information, and design documents.

Work on complex problems where analysis of situations or data requires an in-depth evaluation of several factors.

Self-learner, flexible and able to work in a multi-tasked and dynamic environment.

Excellent communication skills: demonstrated ability to explain complex technical concepts to both technical and non-technical audiences.

8+ years of experience with application development using Python, Java, RESTful services, high-performance, and multi-threading.

Familiarization with DevOps tools and concepts such as Infrastructure as code, Jenkins, Ansible, and Terraform.

You have experience in a Web based environment utilizing React, Angular, server-side rendering, HTML, CSS, JavaScript and TypeScript.

You have knowledge and experience with build tools such as Gradle and Maven.

Familiarity with cloud platforms (e.g., OCP, AWS, Azure, GCP).

You are familiar with modern version control system such as Git.

Strong knowledge of statistical analysis, data mining, and machine learning techniques.

Experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch).

Knowledge of SQL for data manipulation

Great communication skills, ability to explain predictive analytics to non-technical audience.

Proficiency in data exploration techniques and tools

Familiarity with observability tools and practices.