Sr. Machine Learning Engineer – Biotechnology Research
Daley And Associates is currently conducting a search for a Sr. Machine Learning Engineer to join our client who is a rapidly growing biotechnology firm. The company is a target and biology-first drug discovery organization that applies artificial intelligence and machine learning (AI/ML) methods to common drug development bottlenecks while paying close attention to the seamless integration of biology, chemistry, and computation.
This position is key to executing the core mission of our client by utilizing computation, machine learning and protein structure determination, at scale, to accelerate the discovery of novel small molecule therapeutics.
- This is a complex and innovative approach to small molecule discovery and requires a creative mindset
- This role requires the ability to cooperate with internal stakeholders and manage external partners
- The candidate needs to contribute to developing an appropriate AI/ML framework in a start-up environment while building and managing a team
- The ability to work as part of an agile team that supports fast implementation, rapid decision making while maintaining high level of coordination between internal and external parties
- Work with the team to build and evolve the drug discovery and development platform
- Research, advocate, and implement the best practices (machine learning operations, machine learning design lifecycles, software development lifecycles)
- Collaborate with the cross functional drug discovery team to identify drug discovery bottlenecks and use right tools to address the issues
- Conceptualize, implement, validate, and deploy AI/ML tools and modules and integrate them into the platform
- Extract and cleanse drug discovery data from public or internal repositories, collaborate with external data providers, use the data to train, deploy, and update machine learning models, and build pipelines to automate the process. The machine learning models can include, but are not limited to compound property prediction, affinity modeling, target deconvolution, de novo design, etc.
- Quantify and benchmark model performance, proactively address performance gaps, and deliver validated, top-performing models
- BS (8+ years working experience), MS (5+ years working experience), or PhD (3+ years working experience) in computer science, data science, cheminformatics, or other STEM disciplines with a strong component on artificial intelligence and machine learning
- Strong programing skills with Python, familiar with software development lifecycle models
- Experience on machine learning and deep learning methods, including classical machine learning algorithms, convolutional neural network, recurrent neural network, graph neural network, natural language processing, supervised, unsupervised, and reinforcement learning
- Familiar with multiple frameworks, toolkits, and packages such as scikit-learn, keras, Tensorflow, PyTorch, numpy, scipy, pandas
- Strong problem-solving and good communication (verbal and written) skills
- Open minded, willing to learn, and able to learn on the fly
- Past productive collaboration with people of diverse technical background
- Nice to have: RDKit, DeepChem, cloud computing, MLOps, AutoML
For immediate consideration please email your resume to Ryan at email@example.com