Develop and implement machine learning models and algorithms to solve complex business problems
Drive data-driven decision-making
Collaborate closely with data scientists, software engineers, and stakeholders
Deploy machine learning solutions in production environments
Requirements
ML experience with both classical ML and deep learning (PyTorch/TensorFlow)
Proven track record shipping ML products end-to-end
Optimization and causal inference expertise including multi-objective optimization, constraint satisfaction, and counterfactual/scenario modeling for decision support systems
Familiarity with LLMs and generative AI with basic understanding of how to integrate LLM APIs
Strong software engineering fundamentals with ability to handle messy real-world data
Experience with data preprocessing, feature engineering, and data visualization
Understanding of supervised and unsupervised learning techniques
Familiarity with deep learning architectures and neural networks
Proficiency in using cloud platforms (e.g., AWS, Azure, GCP) for model deployment and scaling
Strong problem-solving skills with complex, unstructured data
Excellent communication and teamwork skills
Experience with version control systems like Git
Knowledge of data privacy and security considerations in machine learning
Ability to work independently and adapt to fast-paced projects
Benefits
100% remote/work-from-home role
Temporary 6 month contract
Supportive work environment
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.