ML/AI Engineer – Data, Front-End Integration

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🕒 October 23, 2025

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Softgic

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2011

🔒 Cybersecurity

🤖 Artificial Intelligence

Cloud • Cybersecurity • Artificial Intelligence

Softgic is a technology company focused on driving digital and cognitive transformation for its clients. With over 12 years of experience, Softgic provides innovative and tailored solutions across various areas, including software development, cloud data security, the metaverse, and automation. Their approach combines design, coding, and implementation to enhance business processes and ensure security and efficiency in technological infrastructure.

📋 Description

• Design, train, and implement machine learning and AI models that support real-time decision-making. • Prepare, clean, and structure large-scale datasets in collaboration with data engineers using Snowflake and MongoDB. • Apply the Elastic Hierarchy framework to perform feature engineering and attribution across reconciled datasets. • Build and optimize agent-based workflows connecting ML models to front-end and client systems. • Create and manage JSON-based data payloads for model integration within enterprise workflows. • Integrate ML outputs into React-based front-end applications for visualization, analytics, and interactive use. • Deploy, monitor, and optimize ML models in production using AWS Lambda, EC2, and EKS/Kubernetes. • Ensure reproducibility, version control, and documentation across all ML development workflows. • Collaborate with cross-functional teams (product, data, and engineering) to deliver AI-powered product strategies. • Apply governance, auditability, and compliance standards for ML models used in regulated financial environments.

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. • At least 3 years of experience in machine learning, AI engineering, or data engineering. • Strong programming skills in Python, with expertise in libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch. • Hands-on experience with Snowflake and MongoDB for feature engineering and data preparation. • Familiarity with JSON-based APIs and integration between ML pipelines and front-end systems. • Experience deploying ML services on AWS (Lambda, EC2, EKS/Kubernetes). • Knowledge of data mapping, attribution, or reconciliation frameworks (experience in financial services is a strong plus). • Familiarity with AI-assisted development tools such as Cursor or GitHub Copilot is a plus. • Exposure to regulated data workflows such as AML or KYC is an advantage. • Excellent English communication and collaboration skills, both written and verbal.

🏖️ Benefits

• Remote Job