Lead Machine Learning Scientist

Role Description

The Lead Machine Learning Scientist at OneSix works collaboratively to design and develop machine-learning-based solutions for clients. This role is mission-critical, leading project teams, shaping project scopes, and working directly with clients to iterate on solutions. While not a direct people manager, the Lead ML Scientist serves as a technical team lead, providing mentorship, guidance, and strategic direction to team members to ensure successful project delivery. They are responsible for bringing together state-of-the-art solutions to solve our clients' most pressing problems.

• Conduct research and development on AI/ML models to solve complex technical challenges.
• Design, train, and optimize machine learning models for performance, scalability, and efficiency.
• Experiment with state-of-the-art AI techniques, such as deep learning, reinforcement learning, and generative models.
• Work closely with engineers and scientists to integrate models into production environments.
• Analyze and preprocess large datasets to improve model accuracy and robustness.
• Stay updated with advancements in AI and ML and apply new findings to ongoing projects.
• Ensure AI models adhere to ethical AI practices, fairness, and interpretability principles.
• Contribute to technical documentation and research publications when applicable.
• Strong problem-solving skills and analytical thinking.
• Ability to work independently and collaborate with cross-functional teams.
• Effective communication skills for discussing technical concepts and findings.
• Act as a technical lead by guiding and mentoring team members, providing feedback, and fostering collaboration.
• Help shape project scopes, drive technical discussions, and ensure alignment with business goals.

Qualifications

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• 6+ years of hands-on AI/ML experience, with increasing leadership responsibilities.

Requirements

• Strong proficiency in ML tools (e.g., PyTorch, Scikit-learn, Huggingface).
• Advanced programming skills in Python; experience with R and/or C++ is a nice to have.
• Deep understanding of machine learning algorithms, statistical modeling, and optimization techniques.
• Experience scoping and leading machine learning projects from scoping/design through deployment/monitoring.
• Experience deploying ML models in production environments.
• Experience with cloud-based ML infrastructure (AWS, GCP, Azure) and MLOps practices/tools.

Benefits

• Competitive compensation
• Company-paid medical, vision, dental, and wellness benefits for employees
• Company-provided home office equipment
• Flexible vacation and sick days
• Team-oriented and supportive working environment
• Company-sponsored events and swag