Senior FullStack Engineer – React, Node
G2i Inc.
GraphQLJavaScriptMongoDBNode.jsNoSQLPostgresReactSQLTypeScript
ML/AI Engineer – Data, Front-End Integration
Softgic
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $3,000 per month
Job Level
Mid-LevelSenior
Tech Stack
AWSEC2KubernetesMongoDBNumpyPandasPythonPyTorchReactScikit-LearnTensorflow
About the role
- 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 📊 Resume Score Upload your resume to see if it passes auto-rejection tools used by recruiters Check Resume Score
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningartificial intelligencePythonNumPyPandasScikit-learnTensorFlowPyTorchfeature engineeringdata preparation
Soft skills
communicationcollaborationdocumentationversion controlproblem-solvingcross-functional teamworkgovernanceauditabilitycompliancereproducibility
Certifications
Bachelor’s degree in Computer ScienceMaster’s degree in Computer ScienceBachelor’s degree in Machine LearningMaster’s degree in Machine LearningBachelor’s degree in Artificial IntelligenceMaster’s degree in Artificial Intelligence
