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Ml Ai Biotech Jobs (NOW HIRING)

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

$140K - $225K/yr

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively ... Your efforts will contribute to building production-ready ML infrastructure that enables ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening. They are seeking a talented AI/ML Research Engineer to implement ...

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

Biotech Data Engineer Job Type: FTE Work Mode: Remote The Biotech Data Engineer focuses on ... Lead data engineering initiatives that enable AI/ML model development, LLM integrations, and AI ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively ... and deploy ML infrastructure for distributed training and inference across GPU clusters • ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively ... and deploy ML infrastructure for distributed training and inference across GPU clusters • ...

Sarepta Therapeutics

Senior AI/ML Engineer

Cambridge, MA · On-site

$114K - $156K/yr

The successful candidate will deliver prioritized AI/ML use cases-initially focused on R&D ... Experience in the biopharmaceutical or biotechnology industry. * Familiarity with drug discovery ...

KenkoTech Futures

AI Scientist

Santa Clara, CA · On-site

Well-funded AI Biotechnology Company PLEASE FOLLOW THE KENKOTECH PAGE AND CONNECT WITH THE JOB ... Strong programming skills using modern ML frameworks (PyTorch, JAX, etc.) * Experience with ...

KenkoTech Futures

AI Scientist

Sonoma, CA · On-site

Well-funded AI Biotechnology Company PLEASE FOLLOW THE KENKOTECH PAGE AND CONNECT WITH THE JOB ... Strong programming skills using modern ML frameworks (PyTorch, JAX, etc.) * Experience with ...

KenkoTech Futures

AI Scientist

San Francisco, CA · On-site

Well-funded AI Biotechnology Company PLEASE FOLLOW THE KENKOTECH PAGE AND CONNECT WITH THE JOB ... Strong programming skills using modern ML frameworks (PyTorch, JAX, etc.) * Experience with ...

Output, Inc

AI Technical Recruiter

San Francisco, CA

You need to understand both the AI/ML research community and the biotech talent landscape well enough to source, screen, and close candidates who work at the intersection of the two. * You will own ...

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Ml Ai Biotech information

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$37.5K

$122.7K

$196.5K

How much do ml ai biotech jobs pay per year?

As of Sep 2, 2026, the average yearly pay for ml ai biotech in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is an ML/AI biotech professional?

An ML/AI Biotech professional is someone who applies machine learning (ML) and artificial intelligence (AI) techniques to solve problems in biotechnology. This can involve analyzing biological data, developing algorithms for drug discovery, improving diagnostic tools, and automating laboratory processes. These professionals often work at the intersection of computer science, biology, and data science, collaborating with researchers and clinicians to advance innovations in healthcare, agriculture, and pharmaceuticals. Their work helps accelerate discoveries, improve accuracy, and create new opportunities in the life sciences sector.

How do ML/AI biotech professionals typically collaborate with cross-functional teams during a project?

In ML/AI Biotech roles, professionals often work closely with biologists, data scientists, software engineers, and regulatory experts to develop and validate models for biological data analysis. Collaboration usually involves regular project meetings, shared data repositories, and iterative feedback cycles to align technical developments with biological insights and business goals. Effective communication is essential, as team members bring diverse expertise and perspectives, ensuring robust and impactful solutions. This collaborative environment not only enhances project outcomes but also provides valuable learning opportunities across disciplines.

What are the key skills and qualifications needed to thrive as an ML/AI biotech professional, and why are they important?

Success as an ML/AI professional in biotech requires a strong background in computer science, statistics, and biology, often with an advanced degree in a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and bioinformatics tools is essential, along with experience in handling large biological datasets. Strong problem-solving abilities, interdisciplinary communication, and adaptability help professionals collaborate effectively with scientists and clinicians. These combined skills enable the development of innovative solutions for complex biological challenges, driving advancements in biotech research and applications.

What is the difference between Ml Ai Biotech vs Data Scientist?

AspectML AI BiotechData Scientist
Required CredentialsDegree in biotech, computer science, or related fields; knowledge of ML/AI toolsDegree in statistics, computer science, or related fields; proficiency in data analysis
Work EnvironmentBiotech labs, research centers, biotech companiesTech firms, research organizations, healthcare analytics
Industry UsageDevelops AI/ML models for biotech applications like drug discoveryAnalyzes data to inform business or research decisions across industries

ML AI Biotech professionals focus on applying machine learning and AI techniques specifically within the biotech industry, often working on drug discovery and genomics. Data Scientists have a broader role across various sectors, analyzing data to extract insights. While both roles require strong analytical skills, ML AI Biotech specialists typically have specialized knowledge in biotech applications and AI tools tailored for biological data.

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Ml Ai Biotech jobs near you
Infographic showing various Ml Ai Biotech job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

AI/ML Research Engineer

Manifold Bio

Boston, MA • On-site

$140K - $225K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago

Job description

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening to unlock tissue-targeted medicines and organism-scale models of living systems. Using proprietary molecular barcoding technology, we screen hundreds of thousands of protein designs simultaneously in living systems, producing in vivo-validated datasets at a scale no one else can match. The datasets power our computational models, which leads to better drug designs, creating a flywheel that gets stronger with every campaign. Our team of protein engineers, biologists, and computational scientists works across this full stack to pursue programs both internally and with leading pharma companies.
Position
Manifold Bio is seeking a talented Machine Learning Research Engineer to join our growing AI team. You will work closely with our research scientists to implement, scale, and optimize machine learning systems that power our de novo antibody design platform and advance our protein design capabilities. Your efforts will contribute to building production-ready ML infrastructure that enables breakthrough discoveries in protein therapeutics. You will be expected to take ownership of engineering challenges in our ML pipeline, from data processing and model training to deployment and monitoring, while collaborating closely with our research team to translate cutting-edge ideas into robust, scalable systems.
This is an on-site role and can be based in either Boston, Massachusetts or San Francisco, California. Please only apply if you reside in these cities or are open to relocate.
Responsibilities
  • Implement and optimize machine learning models for protein design
  • Build and maintain scalable data processing pipelines for large-scale protein and molecular datasets
  • Develop and deploy ML infrastructure for distributed training and inference across GPU clusters
  • Collaborate with research scientists to translate experimental ML approaches into production-ready code
  • Design and execute ML experiments with clear hypotheses and rigorous analysis
  • Optimize model performance and computational efficiency for large-scale protein design tasks
  • Build tools and utilities to support rapid prototyping and experimentation by the research team

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Computational Biology, or related field
  • 2+ years of hands-on experience with PyTorch and/or JAX for deep learning applications
  • Strong proficiency in Python scientific computing stack (NumPy, Pandas, scikit-learn)
  • Experience with distributed computing and GPU optimization techniques
  • Familiarity with protein structure analysis, computational biology, or analogous problems in natural sciences
  • Understanding of modern deep learning architectures and optimization techniques
  • Experience implementing research papers or translating ML approaches to production systems
  • Proficiency with version control (Git), testing frameworks, and software engineering best practices
  • Strong problem-solving skills and ability to work independently on technical challenges
  • Excellent written and verbal communication skills for cross-functional collaboration

Preferred Qualifications
  • Experience training LLMs or diffusion generative models
  • Knowledge of cloud computing platforms (AWS, GCP) and containerization (Docker, Kubernetes)
  • Background in computational biology, bioinformatics, or structural biology
  • Experience with large-scale data engineering and ETL pipelines
  • Familiarity with MLOps practices and model deployment frameworks

This Role Might Be Perfect For You If
You are passionate about leveraging state of the art machine learning approaches to solve challenging disease areas
  • You enjoy translating research ideas into high impact, productionized, scalable code
  • You have rich AI/ML experience and are looking to pivot into biotech

If you're excited to build scalable ML systems that revolutionize protein therapeutic discovery, please reach out to careers@manifold.bio.
Base Salary Range: $140,000-225,000
This reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate's experience, interview performance, and expected impact.
This role is eligible for:
  • Annual performance-based target bonus
  • Stock options
  • Comprehensive medical, dental, and vision coverage
  • 401(k) plan
  • Flexible paid time off and holidays
  • Perks including on-site gym, onsite lunch, and commuter support

Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.
We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.

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