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Biology Machine Learning Intern Jobs (NOW HIRING)

Machine Learning Intern (R&D) Location: 5-days in NY office Job Type: Full time (June 15 - Aug 14, 2026) Job Reports To: Director of AI Salary Range: $30.00-$35.00/hr. About Jaan Health/Phamily Jaan ...

The research intern will be in a fast-paced start-up environment playing a crucial technical role ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

The research intern will be in a fast-paced start-up environment playing a crucial technical role ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

The research intern will be in a fast-paced start-up environment playing a crucial technical role ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

The Opportunity Adobe is looking for a Machine Learning intern who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience ...

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Biology Machine Learning Intern information

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$25.5K

$42.6K

$88K

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

As of May 28, 2026, the average yearly pay for biology machine learning intern in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Biology Machine Learning Intern, and why are they important?

To thrive as a Biology Machine Learning Intern, you need a foundational understanding of biology, statistics, and programming (usually Python or R), often supported by coursework or a degree in a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), bioinformatics tools, and data analysis platforms is typically expected. Strong problem-solving abilities, attention to detail, and teamwork skills help interns excel in interdisciplinary research environments. These skills and qualities are crucial for effectively analyzing biological data, developing models, and contributing to innovative scientific solutions.

What kinds of projects do Biology Machine Learning Interns typically work on, and how do these projects contribute to the team?

Biology Machine Learning Interns often work on interdisciplinary projects that apply machine learning techniques to analyze biological data, such as genomics, protein structures, or cellular imaging. These projects may involve developing predictive models, automating data processing pipelines, or extracting meaningful patterns from large, complex datasets. Interns usually collaborate closely with both biologists and data scientists, gaining hands-on experience and contributing valuable insights that support ongoing research or product development. This collaborative environment not only enhances technical skills but also provides exposure to real-world applications of AI in life sciences.

What does a Biology Machine Learning Intern do?

A Biology Machine Learning Intern works at the intersection of biology and computer science, applying machine learning techniques to analyze biological data. Their tasks often include processing large datasets, building predictive models, and supporting research projects that use artificial intelligence to solve biological problems. Interns may work on projects like drug discovery, genomics, or protein structure prediction, and typically collaborate with scientists and engineers. This role helps bridge the gap between experimental biology and data-driven insights.
More about Biology Machine Learning Intern jobs
What cities are hiring for Biology Machine Learning Intern jobs? Cities with the most Biology Machine Learning Intern job openings:
What states have the most Biology Machine Learning Intern jobs? States with the most job openings for Biology Machine Learning Intern jobs include:
Infographic showing various Biology Machine Learning Intern job openings in the United States as of May 2026, with employment types broken down into 74% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 95% Physical, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Intern (R&D)

Machine Learning Intern (R&D)

Phamily

New York, NY โ€ข On-site

$30 - $35/hr

Full-time, Internship

Posted 8 days ago


Job description

Machine Learning Intern (R&D)
Location: 5-days in NY office
Job Type: Full time (June 15 - Aug 14, 2026)
Job Reports To: Director of AI
Salary Range: $30.00-$35.00/hr.
About Jaan Health/Phamily
Jaan Health is a leading AI-based care management company serving healthcare providers. For nearly a decade, the company has leveraged its easy-to-use, proprietary technology to enable health systems, medical groups, and ACOs to deliver high-quality, high-ROI proactive care to hundreds of thousands of previously underserved patients.
Phamily, the company's core technology platform, has transformed chronic disease management with clinically tested AI and easy-to-use technology that enables physicians and care teams to offer high-touch, individualized patient care that has been proven to reduce investment in extra labor and the overall cost of care. Phamily helps ensure healthcare providers are compensated fairly for providing high-quality care between office visits, while improving the lives of patients with chronic diseases. Learn more at phamily.com.
Job/Role Description:
Jaan Health is building AI-powered infrastructure to transform healthcare from reactive treatment to proactive care. Our platform, Phamily, helps providers manage chronic conditions at scale-improving patient outcomes while reducing costs.
We are looking for a Machine Learning Intern to work at the intersection of applied research and production systems, helping us advance cutting-edge AI in real-world healthcare environments. This role provides hands-on experience building, evaluating, and improving machine learning systems that directly impact patient outcomes and operational efficiency.
Key Responsibilities:
โ€ข Design and prototype novel ML approaches, especially in NLP, LLMs, and transformer architectures for healthcare use cases.
โ€ข Conduct applied research through experimentation, evaluation, and model iteration.
โ€ข Develop prompting strategies, fine-tuning techniques, and retrieval workflows.
โ€ข Translate research findings into scalable production-oriented systems.
โ€ข Build evaluation frameworks connecting model performance to healthcare outcomes.
โ€ข Collaborate with engineering and product teams to deploy AI-powered features.
โ€ข Work with large, real-world healthcare datasets and derive actionable insights.
โ€ข Document methodologies, findings, and technical recommendations.
Requirements:
โ€ข MS or PhD candidate in Machine Learning, Computer Science, or related field
โ€ข Strong background in deep learning, NLP, and/or LLMs
โ€ข Hands-on experience with PyTorch / TensorFlow / Hugging Face
โ€ข Proven ability to run experiments and derive insights from data
โ€ข Solid Python skills and comfort working with real-world, messy datasets
โ€ข Interest in bridging research โ†’ production impact
Preferred Requirements:
โ€ข Experience with conversational AI
โ€ข Experience with LLM evaluation, fine-tuning, or retrieval systems
โ€ข Exposure to healthcare data or applied ML in regulated domains
Work Style:
We are a fast-growing, early-stage company with a bold mission and significant work ahead; every employee at Jaan Health must embody growth company DNA. This means you have proven success in a high-performing environment: high velocity, strong ownership, comfort with ambiguity, resilience, and a true growth mindset.
You are both a playbook builder and executor, able to design scalable approaches for today while anticipating what the business will need tomorrow, and then follow through to deliver results.
Our culture is built on five principles that shape how we work, lead, and grow:
โ€ข Care: We put patients, clients, teammates, and outcomes first.
โ€ข Curiosity: We ask better questions, challenge assumptions, and keep learning.
โ€ข Clarity: We simplify complexity, communicate directly, and create alignment.
โ€ข Co-Creation: We collaborate across teams, perspectives, and disciplines.
โ€ข Craftsmanship: We execute with excellence, ownership, and continuous improvement.
What You'll Gain
Through this internship, you will gain:
โ€ข Work on high-impact, real-world AI problems in healthcare
โ€ข Own projects that go from research ideas โ†’ deployed systems
โ€ข Collaborate with a fast-moving, product-driven ML team
โ€ข Real-world experience in a fast-paced, high-growth environment
โ€ข Exposure to executive leaders and cross-functional teams
โ€ข Mentorship and professional development support
โ€ข Experience solving real business challenges
โ€ข Stronger communication, collaboration, and problem-solving skills
โ€ข Opportunity to build confidence, ownership, and business acumen
โ€ข A collaborative, mission-driven team helping transform healthcare at scale
If you take pride in delivering results, embrace challenges, and proactively seek improvement, then this is the place for you. You'll join a smart, humble, and collaborative team dedicated to improving healthcare.
Equal Employment Opportunity
Phamily is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, genetics, veteran status, sexual orientation, gender identity or expression, or any other legally protected status.