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Machine Learning Engineer Biotech Jobs (NOW HIRING)

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Roberts Recruiting

Machine Learning Engineer

Boston, MA · On-site

As a machine learning engineer, you will develop natural language processing systems that help our customers understand their contracts. You will work with a wide range of structured and unstructured ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

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All JobsMachine Learning Engineer Biotech Jobs

Machine Learning Engineer Biotech information

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$31.5K

$128.8K

$193.5K

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

As of Jul 5, 2026, the average yearly pay for machine learning engineer biotech in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 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.

More about Machine Learning Engineer Biotech jobs
What cities are hiring for Machine Learning Engineer Biotech jobs? Cities with the most Machine Learning Engineer Biotech job openings:
What are the most commonly searched types of Machine Learning Engineer Biotech jobs? The most popular types of Machine Learning Engineer Biotech jobs are:
What states have the most Machine Learning Engineer Biotech jobs? States with the most job openings for Machine Learning Engineer Biotech jobs include:
What job categories do people searching Machine Learning Engineer Biotech jobs look for? The top searched job categories for Machine Learning Engineer Biotech jobs are:
Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in the United States as of June 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Spotify

Remote

Full-time

Posted 22 days ago

Job description

Job Summary:
Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of promotional strategies and providing actionable insights to customers.
Responsibilities:
• Contribute to the design, build, evaluation, shipping, and refinement of systems that improve Spotify’s promotional performance with hands-on ML development
• Collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring they are highly efficient, scalable, and consistently meet well-defined success criteria
• Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures.
• Work with Data and ML Engineers to support transitioning machine learning models from research and development into production
• Implement and monitor model success metrics, diagnose issues, and contribute to an on-call schedule to maintain production stability.
Qualifications:
Required:
• Experience implementing ML systems at scale in Java, Scala, Python or similar languages
• Experience with ML frameworks such as TensorFlow, PyTorch, etc.
• Understanding of how to bring machine learning models from research to production
• Collaborative mindset, enjoy working closely with research scientists, machine learning engineers, and data engineers
• Experience in optimizing machine learning models for production use cases
• Familiarity with creating model success metric dashboards
• Willingness to take part in an on-call schedule to maintain performance
Preferred:
• Experience with data pipeline tools like Apache Beam, Scio
• Experience with cloud platforms like GCP
• Exposure to causal ML models, including things like counterfactuals
Company:
Spotify is a commercial music streaming service that provides restricted digital content from a range of record labels and artists. Founded in 2006, the company is headquartered in Stockholm, SWE, with a team of 5001-10000 employees. The company is currently Late Stage.

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