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Machine Learning Biology Jobs in Austin, TX (NOW HIRING)

Apple

Demographic Data Scientist

Austin, TX · On-site

... machine learning within a human factors design team. You'll have the unique opportunity to ... Physics, Biological Sciences, Climate or Environmental Science. Equipped with deep knowledge of ...

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Machine Learning Biology information

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$22.8K

$51.7K

$73.8K

How much do machine learning biology jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning biology in Austin, TX is $51,731.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,600.00 and $60,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in machine learning biology?

Professionals in Machine Learning Biology often deal with challenges such as handling large and complex biological datasets, integrating heterogeneous data types (like genomics, proteomics, or imaging), and addressing the noise and variability inherent in biological data. Interpreting results in a biologically meaningful way and ensuring reproducibility of models can also be complex, requiring close collaboration with experimental scientists. Many teams are cross-functional, so frequent communication with biologists, clinicians, and software engineers is important for project success. While these challenges can be demanding, they also offer opportunities for innovation and significant contributions to scientific discovery or medical advances.

What is a machine learning biology?

A Machine Learning Biology job involves applying machine learning techniques to analyze biological data, such as genomic sequences, protein structures, or medical images. Professionals in this field develop algorithms to identify patterns, make predictions, and derive insights that can advance research in drug discovery, personalized medicine, and biotechnology. These roles typically require expertise in biology, data science, and programming, often using tools like Python, TensorFlow, or scikit-learn.

What are the key skills and qualifications needed to thrive in machine learning biology?

To thrive as a Machine Learning Biology professional, you need expertise in both computational methods (especially machine learning and data science) and a solid understanding of biological sciences, typically supported by an advanced degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and working with biological databases are highly valued. Strong analytical thinking, problem-solving abilities, and effective interdisciplinary communication are key soft skills for this position. These competencies are vital for translating complex biological data into actionable insights and advancing research or product development in biotechnology and life sciences.

What are the most commonly searched types of Machine Learning Biology jobs in Austin, TX? The most popular types of Machine Learning Biology jobs in Austin, TX are:
What are popular job titles related to Machine Learning Biology jobs in Austin, TX? For Machine Learning Biology jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biology jobs in Austin, TX look for? The top searched job categories for Machine Learning Biology jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Biology jobs? Cities near Austin, TX with the most Machine Learning Biology job openings:
Machine Learning Biology jobs near you
Infographic showing various Machine Learning Biology job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $51,731 per year, or $24.9 per hour.

Machine Learning Engineer - Strategic Data Solutions

Apple

Austin, TX • On-site

$113K - $136K/yr

Full-time

Re-posted 2 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!
At Apple, new ideas have a way of quickly becoming outstanding products, services, and customer experiences. Bring passion and dedication to your career, and there's no telling what you could accomplish! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency. Our work touches all parts of Apple, from manufacturing to fulfillment to apps and services. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
As a SDS Machine Learning Engineer, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.
Description
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions
• Collaborate with technical partners to implement robust real-time and batch decisioning in production
• Create reporting and monitor decisioning quality to maintain operational and business metric health
• Investigate trends, assess threat impact, and respond with agile logic changes
• Communicate with stakeholders with varying technical backgrounds and business priorities about your work
• Share what you're learning about novel technologies and methods (in data science, machine learning, data engineering, and software engineering, etc) to improve your team's overall technical capabilities
Minimum Qualifications
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelor's degree with equivalent experience
At least 3 years of practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions
Practical experience with implementing data science-related applications in a programming language such as Python, Scala, or Java
Preferred Qualifications
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses
Ability to use a querying language such as SQL to extract insights from data
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions
Team-oriented skills and values to facilitate effective collaboration with business and technical partners

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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