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Machine Learning Engineer Biotech Jobs in Reno, NV

DataAnnotation

SDLC Engineer - AI Trainer

Sparks, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

SDLC Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Sparks, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

Automated QA Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

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All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Reno, NV

Machine Learning Engineer Biotech information

See Reno, NV salary details

$31.4K

$128.4K

$192.9K

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 Reno, NV is $128,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,200.00 and $154,500.00 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 popular job titles related to Machine Learning Engineer Biotech jobs in Reno, NV? For Machine Learning Engineer Biotech jobs in Reno, NV, the most frequently searched job titles are:
Machine Learning Engineer Biotech jobs near you

Data Engineer

MERCURY GROUP STAFFING AND PLACEMENT SERVICES

Reno, NV • On-site, Remote

$58.83 - $82.37/hr

Full-time

Posted 5 days ago

Job description

Job Title: Data Engineer
Location: Reno, NV (Remote or Hybrid)
Salary Range: $58.83-$82.37 per hour

Primary Responsibilities:

  • Experience with AWS infrastructure including AWS Connect and AWS Lambda.
  • Manage and optimize the movement and validation of data from an Epic EMR system to SQL databases in AWS or Azure and either from or to the Salesforce platform.
  • Accountable for data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance.
  • Oversee the development of novel data pipelines that integrate and normalize large data from a variety of sources to enable learning health, machine learning model development, and deployment.
  • Design, direct, and implement ETL processes, including data capture, data quality, testing, and validation methods.
  • Layer in instrumentation in the development process so that data pipelines can be monitored.
  • Build processes and diagnostic tools to troubleshoot, maintain, and optimize engineering environments and respond to production issues.
  • Provide subject matter expertise and hands-on delivery of data capture, curation, and consumption pipelines for AWS.
  • Participate in deep architectural discussions to build confidence and ensure customer success when building new solutions and migrating existing data applications on the Azure platform.
  • Develop documentation, such as data dictionaries, guides, or data flow diagrams that assist staff in identifying, locating, and using the organizations data.

Incumbent Must Possess:

  • Minimum of 3 years of SQL programming experience and associated SQL tools (SSIS, SSMS, SSRS, etc.).
  • Experience with Visual Studio is preferred.
  • At least 3 years of experience in developing data ingestion, data processing, and analytical pipelines for big data, relational databases, NoSQL, and data warehouse solutions.
  • Minimum of 3 years of RDBMS experience.
  • Extensive hands-on experience implementing data migration and data processing using Amazon Web Services. Includes knowledge of Amazon Connect and Amazon Lambda.
  • Knowledge of medical terminology, especially ICD-10 codes, CPT codes, DRG codes, and an understanding of adjudicated claims data.
  • Excellent verbal and written communication skills.

Minimum Qualifications:

  • Education: Masters degree with 10 years experience preferred; Bachelors degree with 13 years of equivalent experience will be considered in place of masters degree requirement.
  • Experience: Requires a minimum of 10 years experience with at least five (5) years working in data management, data engineering, or data architecture. Enterprise Data Warehouse development preferred; Requires at least five (5) years working with healthcare data; more is preferred. SQL proficiency is required.
  • License(s): None
  • Certification(s): Certification work related to Epic or Amazon Cloud may be required within 1 year of starting employment.
  • Computer / Typing: Must be proficient with Microsoft Office Suite, including Outlook, PowerPoint, Excel, and Word and can use the computer to complete online learning requirements for job-specific competencies, access online forms and policies, complete online benefits enrollment, etc.

This role offers a unique opportunity to work on cutting-edge data engineering projects in the healthcare industry. If you meet the qualifications and are excited about the potential of this role, we encourage you to apply.

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