Machine Learning Engineer
Core
Design, develop, deploy, and support scalable machine learning solutions including predictive models, time-series forecasting, and Generative AI applications.
Role type
Senior Machine Learning Engineer (MLOps & Generative AI)
Builds
Production ML models, reusable pipelines, APIs, and LLM solutions for business stakeholders.
Domain
Cloud-based Machine Learning, MLOps, Generative AI, Time-Series Forecasting
Deliverable
production ML models
Required skills
Python, SQL, Scikit-learn, PyTorch, TensorFlow, XGBoost, feature engineering, hyperparameter tuning, AWS SageMaker, CI/CD, Docker, Git, model monitoring, data drift detection, API development
Preferred skills
Generative AI, Large Language Models, Retrieval-Augmented Generation, vector search, LangChain, Kubernetes, feature stores, regulated industry experience
Technologies
AWS (SageMaker, S3, Lambda, ECR, ECS, EKS, Step Functions, CloudWatch), Python, SQL, Scikit-learn, PyTorch, TensorFlow, XGBoost, Docker, Git, Kubernetes, LangChain, OpenAI GPT, Amazon Bedrock
Responsibilities
Design and deploy predictive models for forecasting, classification, and anomaly detection; build MLOps pipelines for versioning, testing, and automated retraining; develop and monitor production APIs and LLM applications; implement responsible AI and security governance; collaborate with cross-functional teams on technical design and sprint planning.
Seniority
Senior, hands-on IC
