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Machine Learning information
See Lexington, MA salary details
$28.6K - $35K
5% of jobs
$37.2K is the 25th percentile. Wages below this are outliers.
$35K - $41.4K
59% of jobs
$41.4K - $47.8K
9% of jobs
$48.3K is the 75th percentile. Wages above this are outliers.
$47.8K - $54.2K
17% of jobs
$54.2K - $60.6K
4% of jobs
$60.6K - $67K
2% of jobs
$67K - $73.3K
3% of jobs
$73.3K - $79.7K
0% of jobs
$79.7K - $86.1K
0% of jobs
$86.1K - $92.5K
0% of jobs
$92.5K - $98.9K
0% of jobs
$28.6K
$47.8K
$98.9K
How much do machine learning jobs pay per year?
What is a Machine Learning job?
A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.
What are some typical day-to-day responsibilities in a Machine Learning role?
As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.
What are the key skills and qualifications needed to thrive in the Machine Learning position, and why are they important?
To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

Full-time
Posted 29 days 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