ZipRecruiter

Log In

1

Machine Learning Research Intern Jobs in Rancho Cucamonga, CA

Esri

Sr. Generative AI Software Developer

Redlands, CA · On-site

$54.75 - $72.50/hr

Responsibilities : • Develop Python-based machine learning components that enhance how users ... engineers, researchers, Professional Services product teams, and domain experts • Work ...

Esri

Sr. Software Development Engineer - Gen AI

Redlands, CA · On-site +1

$123K - $162K/yr

Develop Python-based machine learning components that enhance how users assess, understand, and ... Work collaboratively with product engineers, researchers, Professional Services product teams, and ...

Esri

Sr. Generative AI Software Developer

Redlands, CA · On-site +1

$54.75 - $72.50/hr

Develop Python-based machine learning components that enhance how users assess, understand, and ... Work collaboratively with product engineers, researchers, Professional Services product teams, and ...

previous page

Showing results 41-60

All JobsMachine Learning Research Intern JobsMachine Learning Research Intern Jobs in Rancho Cucamonga, CA

Machine Learning Research Intern information

See Rancho Cucamonga, CA salary details

$26.1K

$43.5K

$89.9K

How much do machine learning research intern jobs pay per year?

As of Aug 10, 2026, the average yearly pay for machine learning research intern in Rancho Cucamonga, CA is $43,517.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,200.00 and $47,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.
What cities near Rancho Cucamonga, CA are hiring for Machine Learning Research Intern jobs? Cities near Rancho Cucamonga, CA with the most Machine Learning Research Intern job openings:
Machine Learning Research Intern jobs near you
Infographic showing various Machine Learning Research Intern job openings in Rancho Cucamonga, CA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $43,517 per year, or $20.9 per hour.

Postdoctoral Fellow - Modeling Tumor Evolution and Treatment (Hybrid)

City of Hope

Duarte, CA • On-site

$51K - $69K/yr

Other

Re-posted yesterday

City Of Hope rating

8.4

Company rating: 8.4 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

24th of 887 rated healthcare providers

Job description

Postdoctoral Research Fellow - Modeling Tumor Evolution and Treatment 

Join the forefront of groundbreaking research at City of Hope where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research.

The Bild Laboratory at City of Hope uses systems biology to understand how tumors evolve under therapy, uncover resistance mechanisms, and identify actionable vulnerabilities. We integrate longitudinal patient cohorts with single-cell and bulk multi-omics, liquid biopsy, and patient-derived models, partnering closely with clinicians at an NCI-designated Comprehensive Cancer Center.

We are seeking a Postdoctoral Research Fellow to lead computational projects at the interface of tumor evolution, liquid biopsy, and machine learning. The successful candidate will develop and apply methods that integrate multimodal molecular and clinical data (genomic, epigenomic, transcriptomic) across serial patient timepoints to model tumor population dynamics during treatment and predict clinical outcomes. This is a highly collaborative, translational role for a scientist who wants to connect methods development with impactful questions in cancer biology.

Learn more about Dr. Bild's lab here.

As a successful candidate you will:

  • Build probabilistic models of tumor dynamics from serial ctDNA and tissue samples.

  • Develop deep learning frameworks that integrate multimodal data to predict therapeutic response.

  • Construct scalable pipelines for analyzing large longitudinal genomic cohorts.

  • Validate computationally derived biomarkers in collaboration with experimental and clinical teams.

  • Publish in high-impact journals and present at major conferences.

  • Mentor junior lab members.

  • Develop an independent research direction that positions you for a faculty or senior industry role.

Your qualifications should include:

  • A PhD (or equivalent) in computational biology, bioinformatics, systems biology, biomedical engineering, statistics, computer science, or a closely related quantitative field.

Demonstrated expertise across most of the following areas:

Cancer biology domain knowledge

  • Working understanding of tumor evolution and clonal dynamics, pathway and signaling biology in the context of the hallmarks of cancer, and the molecular biology connecting DNA mutation and methylation to RNA and protein function.

  • Familiarity with liquid biopsy modalities (ctDNA, cfDNA methylation, CTCs) and their clinical applications, along with awareness of oncology biomarker validation frameworks, is strongly preferred.

Computational and machine learning skills

  • Proficiency in large-scale genomic data management and bioinformatic processing, including fluency with R/Bioconductor workflows and Python scientific stacks.

  • Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow, and ideally with probabilistic programming tools such as Pyro or Stan.

  • Experience with multimodal data fusion and building efficient, scalable data pipelines for large genomic datasets.

Statistics and mathematics

  • Strong grounding in multivariate statistics, dimensionality reduction, and latent variable modeling.

  • Experience with temporal or dynamical modeling, Bayesian inference, and survival analysis for clinical outcome data.

Scholarly record and collaboration

  • A track record of first-author peer-reviewed publications (or preprints) appropriate to career stage, and the communication skills to work effectively across a team that spans multiple disciplines.  

City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location.

City of Hope is an equal opportunity employer.

To learn more about our Comprehensive Benefits, please CLICK HERE.

#PD

What City Of Hope employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

City of Hope logo

About City of Hope

Sourced by ZipRecruiter

City of Hope is an independent biomedical research and treatment organization for cancer, diabetes and other life-threatening diseases. Founded in 1913, City of Hope is a leader in bone marrow transplantation and immunotherapy such as CAR T cell therapy. City of Hopes translational research and personalized treatment protocols advance care throughout the world. Human synthetic insulin, monoclonal antibodies and numerous breakthrough cancer drugs are based on technology developed at the institution. AccessHope, a subsidiary launched in 2019 serves employers and their health care partners by providing access to City of Hopes specialized cancer expertise. City of Hope is ranked among the nations Best Hospitals in cancer by U.S. News & World Report and received Magnet Recognition from the American Nurses Credentialing Center. Its main campus is located near Los Angeles, with additional locations throughout Southern California and in Arizona.

Industry

Hospitals

Company size

1,001 - 5,000 Employees

Headquarters location

Duarte, CA, US

Year founded

1913

View All City of Hope Jobs

Apply