Description

You will design system solutions and develop custom applications to transition legacy monolithic platforms to event-driven, microservices-based architectures. You own the end-to-end ML engineering lifecycle, from model design to production support.

Responsibilities

• Design software applications and system architecture based on user needs and legacy modernization goals.
• Develop, debug, and document code while collaborating with SRE teams for deployment and monitoring.
• Assess application performance, validate component integration, and produce process flow diagrams.
• Test engineering resilience of software and automation tools, providing post-implementation production support.

Required Skills

• 7-10+ years of software development experience, including leading engineering and scrum teams.
• 4+ years of end-to-end ML engineering, including design, development, and implementation of AI/ML models.
• Applied experience with Statistics and AI/ML models such as Classification, Clustering, and Regression.
• Hands-on experience writing complex SQL using Hive or PySpark-dataframes and optimizing joins for large datasets.
• Expertise in data structures, data modeling, and software architecture.
• Proficiency with SQL, Hadoop, and NoSQL databases.
• Experience with UNIX and GitHub.
• Bachelor’s degree in engineering, computer science, or equivalent, or a Master’s in Computer Applications.

Preferred Skills

• Experience with cloud platforms (GCP/AWS) and building microservices.
• 2+ years of experience designing solutions using Kafka streams or queues.
• Experience with NoSQL databases such as HBase, Couchbase, or MongoDB.

Key Skills

Education

Any Graduate