Machine Learning Engineer - Planet Pharma : Job Details

Job Description We are looking for talented Machine Learning Engineers to join Prescient Design, a division devoted to developing structural and machine learning based methods for molecular design within Research and Early Development organization. The successful candidate will manage projects deploying new techniques for machine learning based molecular optimization for the analysis and design of small and large molecule drugs within target-driven design campaigns. Special focus will be given to engineering pipelines for probabilistic molecular property prediction and Bayesian acquisition for active learning based drug discovery. Additional activities may extend to include engineering pipelines for molecular generative modeling. The Role: ? You will join Prescient Design within the Computational Sciences organization in R&D. Your peers will be machine learning scientists, engineers, computational chemists, and computational biologists. ? You will closely collaborate with scientists within Prescient and across R&D. ? You will develop machine learning and Bayesian optimization workflows to analyze existing, and design new, small and large molecules. ? You will be expected to form close working relationships with small molecule and protein therapeutic development efforts across the R&D organization. ? You will be expected to work on existing projects and generate new project ideas. Qualifications: ? PhD degree in a quantitative field (?e.g.?, Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS degree and 3+ years of industry experience. ? Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases) ? Record of achievement, including at least one high-impact first author publication or equivalent. ? Excellent written, visual, and oral communication and collaboration skills. Additional desired qualifications: ? Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g., rdkit) ? Previous focus on one or more of these areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, statistical methods. ? Public portfolio of computational projects (available on e.g. GitHub). Pay Rate Range: $50-68/hr depending on experience Equal Opportunity Employer: We are proud to be an equal opportunity employer. We welcome and encourage applications from all qualified candidates regardless of race, sex, gender identity or expression, disability, age, religion or belief, sexual orientation, or any other characteristic protected by applicable laws and regulations. It is our policy not to discriminate against any applicant or employee, and we are committed to fostering a diverse, inclusive, and respectful work environment across all locations in which we operate. We believe that diversity, equity, and inclusion are fundamental to our mission and enhance our ability to serve clients globally. If you have a disability or require any reasonable accommodations during the application or interview process, please inform your recruiter or contact us directly so that we can explore the appropriate arrangements. Fraud Alert: Candidate safety is a top priority at Planet Pharma. The industry has seen an increase in people falsely representing themselves as recruiters to gather personal information from job seekers. For your safety, do not provide sensitive data to anyone you have not spoken with thoroughly, never provide banking information during the application process and always double check the email address of the Recruiter to ensure it's from an official Planet Pharma domain (@planet-pharma.com, @planet-pharma.co.uk, and @ppgadvisorypartners.com) and not a domain with an alternative extension like .net, .org or .jobs.