Machine Learning Engineer; Remote

Experience Required
:
Minimum 3–5 years in machine learning development and deployment

About the Role
:

Radar Hire is seeking a skilled and forward-thinking Machine Learning Engineer to design, develop, and deploy scalable ML models and AI-powered solutions for innovative, data-driven companies. This is a hands‑on, engineering-focused role where you’ll take ownership of the entire ML lifecycle—from data ingestion and model training to deployment and monitoring.

The ideal candidate is fluent in modern ML frameworks, understands real‑world application constraints, and is passionate about solving complex problems using predictive modeling, LLMs, or other machine learning methods.

• Design, build, and train machine learning models for classification, regression, clustering, recommendation systems, or generative tasks
• Work closely with data scientists and engineers to prepare and preprocess datasets for modeling
• Implement and optimize training pipelines for experimentation and version control
• Deploy ML models to production using containerization, CI/CD pipelines, and cloud services
• Monitor performance, retrain models as needed, and ensure system stability post-deployment
• Collaborate with product, engineering, and analytics teams to align models with business goals
• Stay up to date with state-of-the-art ML algorithms, tools, and research
• Document model architecture, assumptions, validation metrics, and maintenance plans

• 3–5+ years of hands‑on experience in machine learning model development
• Proficiency in Python and ML libraries such as scikit-learn, Tensor Flow, PyTorch, XGBoost
• Strong understanding of supervised and unsupervised learning techniques
• Experience with data preprocessing
  , feature engineering
  , and model evaluation
• Solid grasp of ML system design, model deployment, and MLOps best practices
• Familiarity with Docker
  , Kubernetes
  , and cloud services (AWS, GCP, or Azure)
• Comfortable working with structured and unstructured data
• Strong collaboration and communication skills in cross‑functional, remote environments

• Experience with LLMs (Large Language Models), embeddings, or vector search integration
• Familiarity with Retrieval‑Augmented Generation (RAG) architectures
• Experience using MLflow
  , Weights & Biases
  , or similar model tracking tools
• Understanding of privacy and compliance considerations for ML systems (HIPAA, GDPR, etc.)
• Exposure to real‑time ML applications (recommendation engines, fraud detection, etc.)

Working Hours

Aligned with U.S. business hours

Why Join

Direct access to results‑driven, growth‑oriented entrepreneurs

Clear expectations and goals with opportunity to make an immediate impact

Work with autonomy and be a key player in scaling a business

• Competitive compensation based on experience and technical capabilities
• Flexible remote‑first work environment
• Access to cutting‑edge projects across diverse industries
• A high‑performance team that values clarity, autonomy, and execution
• Long‑term growth potential and leadership opportunities for standout contributors