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Machine Learning Engineer Biotech Jobs in Arizona

Machine Learning Engineer

Phoenix, AZ

$55.25 - $73.25/hr

Machine Learning Engineer Location: Phoenix, AZ (Onsite) Required Skills Machine Learning, Python, SQL, APIs, NLP, NoSQL, Spark / PySpark, CI/CD We are looking for a strong Machine Learning Engineer ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

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Machine Learning Engineer Biotech information

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 Arizona? The most popular types of Machine Learning Engineer Biotech jobs in Arizona are:
What cities in Arizona are hiring for Machine Learning Engineer Biotech jobs? Cities in Arizona with the most Machine Learning Engineer Biotech job openings:

$55.25 - $73.25/hr

Other

Posted 23 days ago


Job description

Machine Learning Engineer

Location: Phoenix, AZ (Onsite)

Required Skills

Machine Learning, Python, SQL, APIs, NLP, NoSQL, Spark / PySpark, CI/CD

Job Description

We are looking for a strong Machine Learning Engineer with hands-on experience in developing, deploying, and optimizing ML models in enterprise environments. The ideal candidate should have expertise in Classical Machine Learning, NLP, Python development, and scalable data processing systems.

Required Qualifications

Bachelor s or higher degree in Data Science, Computer Science, Engineering, Information Systems, or related field

Hands-on experience building and deploying Machine Learning models including Classical ML and NLP solutions

Strong understanding of ML algorithms, frameworks, libraries, and software architecture

Advanced Python programming experience; Java knowledge is a plus

Experience integrating ML models into existing applications in both batch and real-time environments

Strong SQL skills with experience writing complex queries and optimizing data pipelines

Experience with NoSQL databases is a plus

Familiarity with Big Data technologies such as Spark, PySpark, Hive, MapReduce

Working knowledge of UNIX/Linux commands

Experience using GitHub and CI/CD pipelines

Strong analytical, problem-solving, and communication skills

Experience with AI/ML governance in regulated industries is a plus

Preferred Experience

NLP model development

Enterprise-scale ML deployments

Real-time inference/API integrations

Financial services or highly regulated industry background