(Immediate Start) Senior AI / ML Software Engineer

The Company

Cableteque comprises an international team with extraordinary wire interconnects, CAD deployments, and AI / ML expertise. Our team is located worldwide, including the US, Europe, and Asia. This enables us to assemble diverse perspectives, comprehensive knowledge, and specialized expertise to deliver the best software products and services to our customers.

Cableteque specializes in offering Predictive Interconnect Analytics (PIA) as a SAAS solution for the electronics OEM industry to address challenges in interconnect design. PIA provides comprehensive design optimization, CAD validation, subject-matter expertise, and design enhancements for complex interconnect systems, ultimately improving effectiveness and predictability. By partnering with industry key players, Cableteque helps OEMs focus on the interconnect's purpose while reducing the risk of costly mistakes and delays in the product design cycle.

Role Overview

We are seeking a Senior AI / ML Software Engineer to join our globally distributed team. In this role, you will lead the design and implementation of machine learning pipelines and AI-driven solutions that power next-generation interconnect design tools. You will work across both back-end and front-end systems to deliver robust, scalable, and intelligent software solutions.

Responsibilities

• Design, develop, and deploy AI / ML models, data pipelines, and intelligent analytics for the PIA platform.
• Architect and optimize end-to-end ML workflows, including data ingestion, model training, evaluation, and deployment.
• Work closely with CAD, data, and product teams to integrate ML-driven decision systems into engineering workflows.
• Develop and maintain high-performance back-end systems in Python 3 using frameworks like FastAPI and Java (Spring Boot).
• Contribute to front-end development in React for data visualization and interactive ML insights.
• Apply MLOps practices for versioning, testing, and deployment (e.g., MLflow, Kubeflow, Airflow, or SageMaker).
• Ensure software scalability and reliability across cloud environments (AWS, GCP, Azure).
• Participate in code reviews, system design discussions, and cross-functional technical planning.

Qualifications

1. Supervised and unsupervised learning

2. Feature engineering and dimensionality reduction

3. Model optimization and hyperparameter tuning

4. Ensemble methods (e.g., Gradient Boosting, Random Forests)

The candidates will be required to complete an assignment as a prerequisite for the interview.

Good luck