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Research Engineer Jobs in Boston, MA (NOW HIRING)

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

They are seeking a talented AI/ML Research Engineer to implement, scale, and optimize machine learning systems that enhance their protein design capabilities, contributing to the development of ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

They are seeking a talented Machine Learning Research Engineer to implement, scale, and optimize machine learning systems that power their antibody design platform and advance protein design ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

They are seeking a talented Machine Learning Research Engineer to implement, scale, and optimize machine learning systems for their antibody design platform and advance protein design capabilities.

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

$140K - $225K/yr

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 ...

Accenture

Senior Advanced AI Research Engineer

Boston, MA · On-site

$113K - $155K/yr

As a Senior Advanced AI Research Engineer, you sit at the boundary between AI systems research and production platform engineering. You investigate hard, open problems in agentic AI - and you close ...

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All JobsResearch Engineer JobsResearch Engineer Jobs in Boston, MA

Research Engineer information

See Boston, MA salary details

$40.2K

$115.2K

$154.8K

How much do research engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for research engineer in Boston, MA is $115,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $113,000.00 per year, depending on experience, location, and employer.

What is a research engineer?

Research engineers are professionals who apply scientific and engineering principles to conduct research, develop new products, and improve existing technologies. They typically work in laboratories, research and development departments, or academic settings, collaborating with scientists and other engineers. Their work often involves designing experiments, analyzing data, and creating prototypes to solve technical problems or advance knowledge in their field.

How do research engineers typically collaborate with cross-functional teams during a project?

Research Engineers often work closely with scientists, data analysts, product managers, and software engineers to develop and implement innovative solutions. Collaboration usually involves regular meetings to align on project goals, sharing technical findings, and integrating research outcomes into product development. Effective communication and the ability to translate complex research concepts into actionable insights are key to ensuring the project progresses smoothly and meets its objectives.

What are the key skills and qualifications needed to thrive as a research engineer, and why are they important?

To thrive as a Research Engineer, a strong background in engineering principles, advanced mathematics, and scientific research—often supported by a relevant degree or postgraduate study—is essential. Familiarity with data analysis tools like MATLAB or Python, CAD software, and laboratory instrumentation is typically required, along with experience in technical report writing. Strong analytical thinking, creativity, and effective collaboration skills help Research Engineers excel in multidisciplinary teams. These competencies are vital for developing innovative solutions, advancing technology, and ensuring rigorous, impactful research outcomes.

What is the difference between Research Engineer vs Data Scientist?

AspectResearch EngineerData Scientist
Required CredentialsTypically requires a master's or Ph.D. in engineering, computer science, or related fieldsUsually holds a master's or Ph.D. in statistics, computer science, or related areas
Work EnvironmentResearch labs, R&D departments, technology companiesData analysis teams, analytics departments, tech firms
Employer & Industry UsageUsed in engineering, manufacturing, aerospace, and tech industriesCommon in finance, healthcare, marketing, and tech sectors

Research Engineers focus on developing new technologies, prototypes, and engineering solutions, often working on hardware or system design. Data Scientists analyze large datasets to extract insights, build predictive models, and support decision-making. While both roles require strong technical skills and advanced degrees, their core functions and industry applications differ significantly.

Do I need a PhD to be a research engineer?

A PhD is not always required to become a research engineer, as many roles value relevant experience, technical skills, and a bachelor's or master's degree in engineering, computer science, or related fields. However, some specialized research positions or advanced projects may prefer or require a doctoral degree. Practical skills, problem-solving ability, and familiarity with tools like MATLAB or Python are also important for success in this role.
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The most popular types of Research Engineer jobs in Boston, MA are:

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For Research Engineer jobs in Boston, MA, the most frequently searched job titles are:

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Research Engineer jobs near you
Infographic showing various Research Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $115,158 per year, or $55.4 per hour.

AI/ML Research Engineer

Manifold Bio

Boston, MA • On-site

Full-time

Re-posted 11 days ago

Job description

Job Summary:
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, scale, and optimize machine learning systems that enhance their protein design capabilities, contributing to the development of production-ready ML infrastructure for breakthroughs in protein therapeutics.
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
Qualifications:
Required:
• 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:
• 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
Company:
Manifold Bio is building a protein barcoding platform to bring the power of multiplexed measurement. Founded in 2020, the company is headquartered in Boston, USA, with a team of 11-50 employees. The company is currently Early Stage.

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