Website:
coderound.ai
Job details:
🚀 What We’re Building
CodeRound AI matches the top 5% of tech talent with fast-growing, VC-funded product startups.
Leading product companies across the US, UK, EU, UAE, and India have hired senior engineers and ML talent through CodeRound to build intelligent systems and AI-driven products at scale.
🧩 What You’ll Do
- Design, build, and deploy scalable machine learning models for real-world production use cases
- Develop and optimize end-to-end ML pipelines — from data ingestion and preprocessing to training and deployment
- Work on large-scale datasets to build predictive models, recommendation systems, NLP, or computer vision solutions
- Collaborate closely with backend, product, and AI research teams to translate business problems into ML solutions
- Deploy and monitor models in production using MLOps best practices
- Improve model performance through feature engineering, hyperparameter tuning, and experimentation
- Build and maintain data pipelines using Python and distributed processing frameworks
- Implement model monitoring, drift detection, and performance tracking systems
- Ensure scalable and reliable ML systems using cloud platforms (AWS/GCP/Azure)
- Take ownership of ML systems end-to-end — from experimentation to production monitoring
✅ You’re a Great Fit If You
- Have 3+ years of experience in Machine Learning or Applied AI roles
- Have hands-on experience building and deploying ML models in production environments
- Are strong in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.)
- Have experience working with large datasets and distributed computing frameworks (Spark, Ray, etc.)
- Understand ML system design, model evaluation, and experimentation frameworks
- Have experience with MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, Vertex AI, etc.)
- Are comfortable working with SQL and data modeling
- Have deployed models via APIs or microservices in production
- Take ownership, think in systems, and raise the overall ML engineering bar
⭐ Good to Have
- Experience with LLMs, Generative AI, or fine-tuning foundation models
- Experience with recommendation systems, ranking systems, or fraud detection
- Exposure to full-stack or backend systems
- Experience building CI/CD pipelines for ML workflows
- Open-source contributions or an active GitHub/Kaggle profile
Click on Apply to know more.