Software Engineering | Automation Engineering | Finance & Operations | Machine Learning | Research & Development | Product Management
Aether's Machine Learning (ML) team is spearheading innovation in the field of enzyme engineering by capitalizing on advanced computational methodologies. Faced with the intricate and multidimensional challenges of enzyme engineering, the ML team employs a suite of refined data-cleaning algorithms to meticulously curate and preprocess extensive volumes of experimental data. By deploying state-of-the-art predictive models, the team has the capability to accurately predict enzyme-substrate interactions, uncover novel enzymatic activities, and optimize enzyme performance across diverse experimental conditions. Furthermore, by utilizing cutting-edge multi-objective search and optimization algorithms, the ML team can concurrently navigate multiple solution spaces, adeptly navigating trade-offs between conflicting objectives to engineer optimal enzyme designs. Aether's innovative fusion of data science and biotechnology is facilitating the creation of pioneering solutions that address pressing challenges within the biotech industry and unleash the boundless potential of enzymes for a wide array of applications.
We are looking for an experienced and highly motivated Data Scientist with a strong background in chemistry to join our ML team. In this role, you will be responsible for developing machine learning models to predict experimental conditions for enzyme-substrate pairs in Matrix-Assisted Laser Desorption/Ionization (MALDI) experiments. Your work will directly contribute to the optimization of enzyme performance and the advancement of our enzyme engineering efforts.
- Development and implementation of machine learning models to predict optimal experimental conditions for enzyme-substrate interactions.
- Propose and test new control strategies for novel chemistries.
- Development of machine learning algorithms to model new classes of chemical reactions, and defining fundamental thermodynamic/physical limits to the types of reactions that are engineerable.
- Collaboration with cross-functional teams, including chemists, biochemists, and data scientists, to define project goals and objectives.
- Analysis and interpretation of experimental data to validate and refine machine learning models.
- Development and maintenance of software tools and pipelines to support data analysis and model training.
- Presentation of research findings and model performance to internal teams and external collaborators.
- Staying current with advances in machine learning, computational chemistry, and enzyme engineering to inform model development and improvement.
- Contributing to the preparation of scientific publications, technical reports, and patent applications.
- Building internal tools for research teams to interpret and categorize data generated by experiments.
You will BRING to this role:
- Master's or Ph.D. in Computational Chemistry, Chemical Engineering, Computer Science, Bioinformatics, or a related field or relevant industry experience
- Demonstrated exceptional output in a relevant field
- Strong understanding of physical chemistry, enzymology, and MALDI mass spectrometry.
- Proven experience developing and applying machine learning models in a chemistry or biochemistry context.
- Proficiency in Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
- Strong problem-solving and critical-thinking skills, with a high level of attention to detail.
- Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team.
- The challenges of a startup excite you. Aether Biomachines is changing the world through a platform that has the potential to revolutionize humanity’s relationship to manufacturing. Our ability to build and maintain scalable and efficient systems to deliver a continuously improving product will be the main differentiator between the success and failure of the organization, and you will be a key stakeholder in this process. You believe you are up to the task and want to prove it.
What to expect:
- Month One:
- Gain a solid understanding of Aether's LIMS system and Automation and Machine Learning workflows.
- Gather requirements from ML and R&D teams for developing predictive models for MALDI experiments.
- Begin development of machine learning models for enzyme-substrate interactions.
- Three Months:
- Refine and validate machine learning models based on experimental data.
- Collaborate with platform teams to optimize experimental conditions for enzyme-substrate pairs.
- Present preliminary model performance results to internal stakeholders.
- Six Months
- Fully integrate machine learning models into Aether's automated laboratory workflows.
- Continue to improve and expand the capabilities of predictive models for enzyme-substrate interactions.
Life at Aether:
- Full suite of health benefits (medical, dental, vision)
- Ancillary benefits, including 401(k), HSA/FSA programs
- Commuter Benefits: Aether will match up to $100/month (Commuter benefits can be allocated towards commute expenses, parking expenses, or both)
- Learning & Development: You may purchase up to $50/month in books or other learning materials without any prior approval
- Access to the gym at our Menlo Park location
- Access to our Menlo Park Labs Shuttle & Parking
- Unlimited PTO and 10 Paid Company Holidays
- Stocked snack cabinet and monthly team bagel breakfast
- Flexible work schedule to accommodate you/your family needs
- Quarterly company-wide events and activities
- Fun--and useful--swag!
This is the pay range for this position that we reasonably expect to pay. Individual compensation is based on various factors, including experience, education, skillset, and geographic location. This range is for the SF Bay Area, California location, and may be adjusted to the labor market in other geographic areas.
SF Bay Area Pay Range
Aether Biomachines, Inc
Aether Biomachines is on a mission to build the post-scarcity future using peptide based nanotechnology as the driving force for the next industrial revolution. By creating the world's most advanced high-throughput robotic laboratory, we are generating data at unprecedented scales to fuel deep learning algorithms. We're assembling a diverse and dynamic team of self-starters, engineers, sci-fi enthusiasts, and visionaries, and we invite you to joi
No. of Employees
Menlo Park, CA, USA