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Machine Learning Engineer Biotech Jobs in Phoenix, AZ

What You'll Do Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see * US: Seattle ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

AI Solutions Architect

Tempe, AZ

$60.25 - $79.50/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

What You'll Do Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see * US: Seattle ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Experience implementing and supporting endtoend Machine Learning workflows and patterns * Expert level programming skills in Python and experience with Data Science and ML packages and frameworks

AI/ML Engineer II

Phoenix, AZ · On-site +1

$113K - $136K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine learning lifecycle to include analysis, solution design, data pipeline engineering, testing ...

AI/ML Engineer II

Phoenix, AZ · On-site

$116K - $139K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine learning lifecycle to include analysis, solution design, data pipeline engineering, testing ...

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Research Engineer

Phoenix, AZ · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Research Engineer

Phoenix, AZ · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Master's degree + 2 years working experience in machine learning * Proficiency in at least one programming language such as Java, Python * Proficiency in big data, the use of frameworks related to ...

Master's degree + 2 years working experience in machine learning * Proficiency in at least one programming language such as Java, Python * Proficiency in big data, the use of frameworks related to ...

... machine learning, computer vision, and self-driving technologies, and apply insights from the ... Python programming with a focus on writing high-quality, well-structured, and tested code ...

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Machine Learning Engineer Biotech information

See Phoenix, AZ salary details

$31.3K

$127.9K

$192.1K

How much do machine learning engineer biotech jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer biotech in Phoenix, AZ is $127,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $153,900.00 per year, depending on experience, location, and employer.

What does a Machine Learning Engineer do in the biotech industry?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do Machine Learning Engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer in Biotech, and why are they important?

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

What is the difference between Machine Learning Engineer Biotech vs Data Scientist Biotech?

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are the most commonly searched types of Machine Learning Engineer Biotech jobs in Phoenix, AZ? The most popular types of Machine Learning Engineer Biotech jobs in Phoenix, AZ are:
What are popular job titles related to Machine Learning Engineer Biotech jobs in Phoenix, AZ? For Machine Learning Engineer Biotech jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Biotech jobs in Phoenix, AZ look for? The top searched job categories for Machine Learning Engineer Biotech jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Machine Learning Engineer Biotech jobs? Cities near Phoenix, AZ with the most Machine Learning Engineer Biotech job openings:
Acceleration Center- Agentic AI and Machine Learning Developer- Experienced Associate

Acceleration Center- Agentic AI and Machine Learning Developer- Experienced Associate

Pwc

Phoenix, AZ

$61K - $100K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 75 frontline employees who took The Breakroom Quiz

21st of 58 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Risk Architecture

Management Level

Associate

Job Description & Summary

The Opportunity
As a Risk Architecture- Agentic AI and Machine Learning Developer- Experienced Associate, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Risk Consulting practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale. Your work will involve designing AI systems, data wrangling, and software implementation to enable the AI models to be useful and scalable.
As an Associate, you will focus on learning and contributing to client engagement and projects while developing your skills and knowledge to deliver quality work. You will be exposed to clients to learn how to build meaningful client connections, manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources. You will be expected to anticipate the needs of your teams and clients, embrace ambiguity, ask questions, and use these challenges as opportunities for growth.
In this role, you will take ownership and consistently deliver quality work that drives value for our clients and success as a team. You will build a brand for yourself, opening doors to more opportunities.
Responsibilities
- Designing and implementing AI and machine learning solutions to transform raw data into actionable insights
- Developing and deploying scalable AI models using programming languages such as Python and Java
- Collaborating with team members to integrate AI systems into existing data infrastructure
- Conducting complex data analysis to identify patterns and inform decision-making processes
- Utilizing machine learning libraries like TensorFlow and Scikit-Learn to enhance model performance
- Building and maintaining data pipelines to support AI and machine learning initiatives
- Engaging in data wrangling and data quality assessments to improve data reliability
- Applying natural language processing techniques to develop advanced text analytics solutions
- Participating in client support activities to address AI-related challenges and opportunities
- Continuously learning and adapting to new AI technologies and methodologies to drive innovation
What You Must Have
- At least a Bachelor's degree
What Sets You Apart
- Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics, Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics, Data Processing/Analytics/Science, Artificial Intelligence and Robotics
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in Python and Java programming languages
- Utilizing machine learning libraries such as TensorFlow and Scikit-Learn
- Engaging in complex data analysis and pattern recognition
- Applying AI implementation skills in client-facing environments
- Developing neural network models for advanced AI solutions

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $61,000 - $100,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.

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