Back-end & ML Engineer: Cloud-Native Systems

2 weeks ago

Bengaluru, Karnataka, India Intellithink Industrial IoT Full time

We are technology-driven company focused on improving the health and efficiency of industrial machinery. We help manufacturing units optimize performance, reduce downtime, and extend equipment life through advanced condition monitoring, predictive maintenance, and AI-powered analytics

We're Hiring: Backend & ML Engineer: Cloud-Native Systems

Experience: 3+ Years

Location: Domlur, Bengaluru

Employment Type: Full-time

Key Responsibilities:

·      Design, develop, and maintain backend services using Node.js , ensuring performance, reliability, and scalability.

·      Build, maintain and update Python codebases and build RESTful APIs in Python

·      Architect and implement RESTful APIs  and microservices  to support application and data workflows.

·      Leverage a suite of AWS services  (e.g., Lambda, EC2, S3, RDS, DynamoDB, SNS/SQS) for cloud-native, serverless, and event-driven architectures.

·      Build and maintain data & ML pipelines  for ingestion, transformation, analysis, and reporting across structured and unstructured sources.

·      Write and optimize complex queries  for analytics, reporting, and business intelligence use cases.

·      Follow and promote best practices  around performance tuning, secure coding, scalability, and testability in distributed systems.

·      Contribute to DevOps efforts , including CI/CD pipelines, infrastructure as code, automated testing, and monitoring (experience here is a strong plus).

Preferred Qualifications:

·      Bachelor's or Master's degree in Computer Science, ECE, Mathematics, Physics, Engineering or related technical discipline.

·      3+ years of experience building production-grade backend systems with Node.js  and JavaScript/TypeScript.

·      Strong proficiency in SQL  and/or NoSQL  databases.

·      Experience with data engineering tools  and frameworks.

·      Solid understanding of signal processing fundamentals , with hands-on experience applying these to real-world data a plus.

·      Familiarity with DevOps  practices and tools (e.g., Docker, GitHub Actions, Terraform, Prometheus, etc.).

·      Strong analytical mindset with a scientific and systematic approach to problem-solving.

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