Lead AI/ML Software Engineer

Job Description The Company Cableteque comprises an international team with extraordinary expertise in wire interconnects, CAD deployments, and AI/ML. 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 Quoteque PIA as a SAAS solution for the electronics industry to address challenges in interconnect design and manufacturing. Quoteque PIA provides comprehensive design-for-manufacturing and sourcing optimization, CAD validation, and subject-matter expertise for complex interconnect systems, ultimately improving effectiveness and predictability. By partnering with industry key players, Cableteque helps OEMs and contact manufacturers focus on the interconnect's purpose while reducing the risk of costly mistakes, delays in the product design cycle, and cost reduction. Role Overview We are seeking a Lead 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-to-manufacturing 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 ML/GenAI models, data pipelines, and intelligent analytics for the Quoteque PIA platform. Architect end-to-end ML/GenAI workflows: data ingestion, training, evaluation, deployment, and monitoring. Partner with data and product teams to integrate ML/GenAI-driven decision systems into user workflows. Build and maintain backend services in Python (FastAPI) and Java (Spring Boot). Contribute to React front-end components for visualization and interactive ML/Gen Ainsights. Apply MLOps best practices (experiment tracking, CI/CD for models, automated retraining) using tools such as MLflow/Kubeflow/Airflow/SageMaker, or similar. Ensure scalability, reliability, and security across cloud environments (AWS/GCP/Azure). Participate in code reviews, system design, and cross-functional technical planning. Qualifications Overall software engineering: 510 years professional experience (min 5 years). Applied AI/ML development: 2+ years delivering models to production. Applied Transformers and embedding-based models: 2+ years, including RAG systems and vector databases (e.g., Milvus, Pinecone). Deep learning: 2+ years with PyTorch, TensorFlow, or Keras (production deployments). MCP: 1+ years. OCR: 1+ years. Python: 510 years (min 5 years) with Python 3.x for data/ML services. MLOps & pipelines: 2+ years implementing training/inference pipelines, versioning, and monitoring using MLflow, Kubeflow, Airflow, or SageMaker. Cloud: Commercial experience on at least one central cloud (AWS 3+ years or Azure/GCP 2+ years). Data tooling: Proficiency with NumPy, Pandas, scikit-learn; SQL proficiency. Communication: At least Professional English (must) Education & Certifications - Required: Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a closely related field. - Nice to have: Degree from a top-tier Indian institute (e.g., IIT, IIIT, VIT) or an equivalent globally recognized university. - Nice to have: Professional certifications such as AWS Certified Machine Learning Specialty, Google Professional Machine Learning Engineer, or equivalent industry credentials. Good luck