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Python Machine Learning Entry Level Jobs (NOW HIRING)

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Proficiency in Python, MLOps (W&B, MLFlow) and ML packages (scikit-learn, PyTorch, JAX), along with ...

Required : • Expertise in Python (including NumPy, pandas, and other packages) • Experience with either PyTorch or TensorFlow • Deep understanding of machine learning fundamentals (gradient ...

Title - Machine Learning ( F2F interview is required) Location - New York, NY ( Hybrid 2-3 days ... Proficient in Python, Pandas, NumPy, Scikit-Learn, PySpark Bachelor s degree in Computer Science ...

Ability to write robust code in Python, Java and R * Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) * Excellent communication skills * Ability ...

This is not an entry-level position, and it is not a principal or architect-level role.. Location ... Python (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred) * Feature ...

Work with tools such as T-SQL, Python, SSIS, Azure Data Factory, and Azure Synapse. * Support ML ... Azure Machine Learning *** ADF or DataBricks *** SQL *** Python Basic Qualification : Additional ...

Qualifications Applicants should have expertise in Python (including NumPy, pandas, and other packages) and either PyTorch or TensorFlow. Deep understanding of machine learning fundamentals (gradient ...

As a machine learning engineer, you will develop natural language processing systems that help our ... Strong Python skills and Python ML stack (pandas, scikit-learn, numpy, etc.) with knowledge of ...

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Python Machine Learning Entry Level information

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How much do python machine learning entry level jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for python machine learning entry level in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Python Machine Learning Engineer, and why are they important?

To thrive as an Entry Level Python Machine Learning Engineer, you need a solid understanding of Python programming, foundational machine learning concepts, and a relevant degree in computer science, statistics, or a related field. Familiarity with tools and libraries such as scikit-learn, TensorFlow, Pandas, and Jupyter Notebooks is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret data and collaborate with technical teams. These skills are crucial for efficiently developing, implementing, and explaining machine learning solutions that meet organizational goals.

What types of projects can I expect to work on as an entry-level Python Machine Learning professional?

As an entry-level Python Machine Learning professional, you will typically work on projects such as data preprocessing, implementing and tuning basic machine learning models, and assisting with feature engineering. You may also be involved in data collection, cleaning, and visualization tasks to support more senior team members. Collaboration is common; you’ll often work closely with data scientists, engineers, and sometimes product managers to deliver actionable insights or build prototype models. This hands-on experience is valuable for building your technical foundation and understanding real-world machine learning workflows.

What are Python Machine Learning Entry Level jobs?

Python Machine Learning Entry Level jobs are positions designed for individuals who are new to the field of machine learning and have foundational programming skills in Python. These roles typically involve tasks such as data preprocessing, implementing basic machine learning algorithms, and assisting with model evaluation and deployment. Entry-level positions often require a basic understanding of statistics, data analysis, and libraries like scikit-learn, pandas, and NumPy. They provide an opportunity to gain hands-on experience while working under the guidance of more experienced data scientists or machine learning engineers.

What is the difference between Python Machine Learning Entry Level vs Data Analyst Entry Level?

AspectPython Machine Learning Entry LevelData Analyst Entry Level
Required SkillsPython, machine learning libraries, basic statisticsExcel, SQL, data visualization tools
CertificationsPython programming, machine learning coursesData analysis certifications, Excel/SQL courses
Work EnvironmentTech companies, startups, research labsBusiness, finance, marketing departments
Job FocusDeveloping ML models, data preprocessingData cleaning, reporting, insights generation

While both roles involve working with data, Python Machine Learning Entry Level focuses on building machine learning models using Python, whereas Data Analyst Entry Level emphasizes data cleaning, analysis, and reporting using tools like Excel and SQL. Both roles require analytical skills, but Python ML roles demand programming and machine learning knowledge, making them more technical.

More about Python Machine Learning Entry Level jobs
What cities are hiring for Python Machine Learning Entry Level jobs? Cities with the most Python Machine Learning Entry Level job openings:
What are the most commonly searched types of Python Machine Learning jobs? The most popular types of Python Machine Learning jobs are:
What states have the most Python Machine Learning Entry Level jobs? States with the most job openings for Python Machine Learning Entry Level jobs include:
Infographic showing various Python Machine Learning Entry Level job openings in the United States as of May 2026, with employment types broken down into 76% Full Time, 14% Part Time, and 10% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.

Machine Learning Engineer

Nanite Inc.

Boston, MA • On-site

Full-time

Posted 25 days ago


Job description

Our mission is to deliver the undeliverable.

 

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. 

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,  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.