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Machine Learning Engineer Biotech Jobs (NOW HIRING)

Willing Tech

Machine Learning Engineer

San Francisco, CA · On-site +1

$172K - $384K/yr

They're now looking for a Machine Learning Engineer to help build the next generation of AI-powered ... IndustriesSoftware Development, Biotechnology Research, and Data Infrastructure and Analytics ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Design and implement complex data engineering processes to support innovative data science modeling ... Interest in applications of machine learning in biotechnology * Strong communication skills, both ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Design and implement complex data engineering processes to support innovative data science modeling ... Interest in applications of machine learning in biotechnology * Strong communication skills, both ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

X4 Engineering

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

🚀 Machine Learning Engineer 📍 Austin, TX (Hybrid/Remote Considered) 💰 $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Spotify

Machine Learning Engineer

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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 ...

Genentech

Machine Learning Engineer

South San Francisco, CA · On-site +1

$168K - $312K/yr

The Machine Learning Engineer sits on the Data Science & Machine Learning Team to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data ...

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All JobsMachine Learning Engineer Biotech Jobs

Machine Learning Engineer Biotech information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Jul 11, 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
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Machine Learning Engineer Biotech jobs near you

Machine Learning Engineer

Willing Tech

San Francisco, CA • On-site, Remote

$172K - $384K/yr

Full-time

Posted 4 days ago

Job description

This range is provided by Willing Tech. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$200,000.00/yr - $300,000.00/yr

Direct message the job poster from Willing Tech

Machine Learning Engineer – Scientific Visualisation Platform

Location: Remote (US/Canada)

Sector: Scientific AI / SaaS

We’re partnering with a pioneering SaaS company at the forefront of AI for scientific communication. Their platform is redefining how scientists present, understand, and share complex biological research—turning experimental protocols, data, and text into clear, editable visuals that accelerate discovery and decision-making.

They're now looking for a Machine Learning Engineer to help build the next generation of AI-powered tools that generate structured visuals from scientific inputs. If you’re excited by real-world, high-impact problems and want to apply machine learning at the intersection of computer vision, scientific research, and design, this is your opportunity.

What You’ll Do

  • Develop machine learning systems that generate structured vector graphics (e.g., SVG/JSON) from biological and textual inputs.
  • Design novel ML architectures focused on scientific diagram generation and natural language-guided editing.
  • Apply the latest in generative AI, computer vision, and multimodal learning to scientific contexts.
  • Collaborate with ML researchers, engineers, and product designers to move from experimentation to scalable deployment.
  • Ensure the visual and biological accuracy, scalability, and editability of AI-generated outputs.

Ideal Candidate

  • 5+ years of experience in machine learning, particularly in computer vision, NLP, or multimodal models.
  • Hands-on experience building and deploying ML systems in production (preferably at a SaaS or product company).
  • Strong coding skills in Python and experience with frameworks like PyTorch, TensorFlow, or JAX.
  • Comfortable with open-ended, technically ambiguous challenges—especially in scientific or research-heavy domains.
  • Bonus: Experience with SVG or vector graphics generation, or a background in life sciences or bio-related research.

Why Join

  • Be one of the first ML hires tackling a completely novel problem in scientific visualisation.
  • Work in a fully remote setup with a smart, mission-aligned team spread across the US and Canada.
  • Shape the technical direction of a product used and loved by scientists around the globe.
  • Join a VC-backed company with an established user base, strong product-market fit, and a clear mission: make science more accessible and actionable.

Interview Insight

We’re looking for engineers who can demonstrate both depth and practicality. Expect conversations around:

  • Your experience with multimodal learning (e.g., combining visual + textual data).
  • Projects where you worked with or generated SVG/vector graphics.
  • The most impactful ML model you’ve developed—metrics, use cases, and why it mattered.

Interested? Let’s connect.

Apply now or reach out directly for a confidential conversation.

Seniority level
  • Seniority levelMid-Senior level
Employment type
  • Employment typeFull-time
Job function
  • Job functionAnalyst, Consulting, and Engineering
  • IndustriesSoftware Development, Biotechnology Research, and Data Infrastructure and Analytics

Referrals increase your chances of interviewing at Willing Tech by 2x

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