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Machine Learning Engineer Biotech information
What does a Machine Learning Engineer do in the biotech industry?
How do Machine Learning Engineers in biotech typically collaborate with research scientists and domain experts?
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer in Biotech, and why are they important?
What is the difference between Machine Learning Engineer Biotech vs Data Scientist Biotech?
| Aspect | Machine Learning Engineer Biotech | Data Scientist Biotech |
|---|---|---|
| Required Credentials | Bachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworks | Bachelor's or Master's in Data Science, Statistics, or related; strong analytical skills |
| Work Environment | Develops ML models, coding, deploying algorithms in biotech R&D | Analyzes biological data, interprets results, creates reports |
| Employer & Industry Usage | Biotech firms, pharma companies, research labs | Biotech companies, healthcare, research institutions |
While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.
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- Flexible Machine Learning
- Weights Biases

Full-time
Posted 16 hours ago
Job description
Our mission is to deliver the undeliverable.
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Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug delivery. The research intern will be in a fast-paced start-up environment playing a crucial technical role in generating cell culture and transfection data. The candidate will work with senior leadership and partner projects gaining broad internal and external exposure.
Essential Functions and Duties
- Design and implement complex data engineering processes to support innovative data science modeling
- Collaborate with chemistry and biology research teams to design data pipelines, analyze experimental data and implement experimentally actionable feed-back loops
- Apply and deploy established and novel statistical and machine learning algorithms to explore, understand and optimize properties of the vast delivery vehicle space, both in silico and experimentally
- Develop robust, scalable workflows and maintain security controls to protect sensitive data across cloud and on-premise environments
- Coordinate with cross-functional teams to deploy models and communicate results and with a focus on computational efficiency, performance, and usability
- Design of repositories, CI/CD pipelines and integration tests for ML workflows
Qualifications
MS in Computer Science, Data Science, Statistics, Computational Biology, Computational Chemistry, or a related discipline with 2 years hands-on machine learning experience.Â
Knowledge, Skills, and Abilities
- Track record developing statistical and machine learning models for complex and unconventional real-life problems
- Strong mathematical and coding skills
- Proficiency in Python, Â MLOps (W&B, MLFlow) and ML packages (scikit-learn, PyTorch, JAX), along with SQL and AWS.
- Familiarity with ML workflow best practices.
- Interest in applications of machine learning in biotechnology
- Strong communication skills, both written and verbal
- Experience doing research and working with interdisciplinary teams
Additional Preferred Experience (desired, but not essential):
- Experience in an industry setting related to biotechnology, chemicals, or materials manufacturing
- Experience with cheminformatics, computational chemistry, computational biology databases, data structures, material science and modelling package
Computer and modeling work required, this is an on-site position based in the Seaport of Boston, MA.
About Nanite
Sourced by ZipRecruiter
Industry
Biotechnology research and development
Company size
11 - 50 Employees
Headquarters location
Boston, MA, US
Year founded
2020