Machine Learning Engineer

Meliora Therapeutics is a next-generation biotechnology company focused on integrating molecular biology and machine learning to combat cancer. They are seeking talented machine learning engineers to develop their core algorithmic engine and contribute to innovative drug discovery methodologies.

Responsibilities:

• Bring your technical skills to bear on a critical problem in cancer treatment that results in 97% of cancer drugs failing their clinical trials
• Develop, implement and validate novel, machine learning-driven methods of associating drugs and their properties with their true mechanism of action in cancer cells
• Lead the development of large-scale machine learning algorithm training and evaluation pipelines
• Grow, learn and contribute to cutting edge platform development that drives drug discovery
• Be a culture-setter by embodying the company’s principles of truth-seeking, mutual respect, integrity, drive, and teamwork

Requirements:

• MS-level expertise in applied machine learning developed either through a formal degree or meaningful experience in performing similar work
• Expertise in the implementation of production-ready advanced machine learning algorithms using TensorFlow, PyTorch, or Jax
• Familiarity with and ability to develop large-scale machine learning systems and workflows including parallel training and evaluation pipelines
• A solid grasp of the fundamentals of machine learning science including broad capability in probability, statistics, machine learning, and programming
• Experience in solving deep technical challenges by helping to develop and validate novel methodologies
• Excellent communication skills to synthesize complex technical problems and solutions into content easily understandable by the scientific and leadership teams to facilitate critical decisions
• Ability to be highly successful operating in a multidisciplinary environment and a willingness to collaborate across functional teams is essential
• Expertise in genomics or cheminformatics isn't necessary to start with, but you will need to be comfortable building an extensive cross-disciplinary background as you go
• Bonus: experience working with biological or *omics datasets and pipelines