Senior Manager, Machine Learning Research

About the Team

Genesis Research offers ML Researchers & Engineers the opportunity to rapidly accelerate the creation of previously impossible medicines. Our work benefits from diverse backgrounds and strong ML expertise because going after undruggable targets requires new ideas.

We are seeking curious explorers who seek the space to try new things with ample support and a path to grow. You’ll bring your ML expertise to the table, collaborating with world class chemists and biologists to manifest the digital domain in the physical world. The result? New treatments for devastating diseases.

The Role As a Senior Manager of ML Research you will lead and shape a Machine Learning Research team, driving the development of innovative models and methodologies for drug discovery. This leadership role involves overseeing teams of ML Research Scientists and Engineers, fostering a culture of collaboration and scientific excellence, and partnering cross-functionally to deliver state-of-the-art machine learning solutions.

This position combines strategic vision, technical leadership, and team mentorship to ensure Genesis Therapeutics remains at the forefront of machine learning for drug discovery.

Responsibilities

• Develop and implement the strategic vision for the ML Research group, ensuring alignment with company goals.
• Serve as a thought leader in state-of-the art ML research, using the latest approaches in diffusion models, equivariant neural nets and predictive ML  Represent Genesis Therapeutics at conferences, workshops, and scientific forums.
• Guide the team in designing, implementing, and validating novel machine learning models tailored to drug discovery challenges, including molecular property prediction, generative modeling, and protein-ligand interactions.
• Prioritize and balance short-term project deliverables with long-term foundational research initiatives.
• Ensure high standards of scientific rigor and reproducibility in research outputs.
• Pioneer cutting edge research and original publications in top industry journals and conferences, including NeurIPS, ICML and more.
• Partner with cross-disciplinary teams, including computational chemists, software engineers, and drug discovery scientists, to deliver impactful ML-driven solutions.
• Collaborate with the Engineering team to deploy ML models into scalable production environments.
• Communicate findings and progress effectively to stakeholders at all levels: from interns to board of directors.
• Manage budgets, resource allocation, and project timelines for the ML Research group.
• Identify and establish external collaborations and partnerships to augment in-house capabilities.
• Lead and mentor a high-performing team of ML Research Scientists and ML Research Engineers.
• Foster a collaborative, innovative, and growth-oriented team culture.
• Manage recruitment, performance evaluations, and career development for team members.

Qualifications

• PhD in Computer Science, Machine Learning, Physics, or a related field.
• 4+ years of professional experience in machine learning research, with at least 1+ years in a tech or people leadership role.
• Strong track record of developing and applying ML methods in areas such as deep learning, generative models, graph neural networks, or equivariant neural networks.
• Proven expertise in leveraging ML techniques for real-world problems. It is not a requirement that our ML leaders have deep experience in the drug discovery domain but must have demonstrated ability to champion great research and intellectual curiosity to learn quickly.
• Experience with state-of-the-art ML frameworks (e.g., PyTorch, TensorFlow, JAX) and distributed computing environments.
• Demonstrated ability to lead, mentor, and inspire a diverse team of researchers and engineers.
• Exceptional communication and collaboration skills, with experience bridging the gap between research and application.
• Strategic thinking with a balance of creativity and execution focus.