We are seeking an exceptionally talented and innovative Machine Learning Scientist to join our clients advanced AI/ML research and development team. In this role, you will be at the forefront of designing, developing, and deploying state-of-the-art machine learning algorithms and models that directly impact our core products and user experiences. You'll blend theoretical expertise with practical engineering skills to tackle challenges that have never been solved before, working with massive datasets and distributed systems.
What You'll Do:
- Research & Innovate: Identify, research, and develop novel machine learning algorithms and models (e.g., deep learning, reinforcement learning, causal inference) to address critical product challenges and unlock new capabilities.
- Model Development & Deployment: Design, train, evaluate, and deploy highly scalable and efficient ML models into production systems, ensuring robustness, performance, and reliability.
- Feature Engineering & Data Understanding: Collaborate with data engineers and data scientists to identify, create, and refine features from vast and diverse datasets to optimize model performance.
- Experimentation & Evaluation: Establish rigorous evaluation methodologies for new models, conduct A/B tests, analyze results, and iterate on solutions based on empirical evidence.
- Cross-functional Collaboration: Work closely with product managers, software engineers, and other research scientists to translate business problems into ML solutions and integrate these solutions into products.
- Stay Cutting-Edge: Keep abreast of the latest advancements in academic and industry ML research, contributing to publications and patents where appropriate, and applying relevant techniques to our challenges.
- Drive Best Practices: Champion best practices in ML model development, MLOps, reproducibility, and ethical AI across the organization.
What You'll Bring:
- Ph.D. or Master's degree in Computer Science, Machine Learning, Statistics, or a closely related quantitative field, with a strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, KDD) or equivalent industry experience.
- 5+ years of experience in applied machine learning research and development, building and deploying ML systems at scale.
- Expert proficiency in Python and popular ML frameworks (e.g., TensorFlow, PyTorch, JAX).
- Solid understanding of core ML concepts: supervised/unsupervised learning, reinforcement learning, deep learning architectures (e.g., Transformers, CNNs, RNNs), Bayesian methods, optimization techniques, and feature engineering.
- Experience with large-scale data processing: Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop) is essential.
- Strong experimental design skills: Ability to set up and analyze A/B tests, understand statistical significance, and interpret results