1

Scientific Machine Learning Jobs in Boston, MA (NOW HIRING)

Support scientific diligence with pharma and clinical partners * Contribute to Nucs AI\'s scientific credibility in the field What You Bring * PhD in machine learning, computer vision, medical image ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Work closely with data scientists, clinicians, and software engineers to understand requirements ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Work closely with data scientists, clinicians, and software engineers to understand requirements ...

Senior Machine Learning Engineer

Boston, MA · Remote

$125K - $165K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Work closely with data scientists, clinicians, and software engineers to understand requirements ...

... machine learning, statistics, estimation theory, and information theory algorithms for signals ... scientific field such as applied math, physics, electrical engineering, computer science, or data ...

... machine learning, statistics, estimation theory, and information theory algorithms for signals ... scientific field such as applied math, physics, electrical engineering, computer science, or data ...

Showing results 21-40

Scientific Machine Learning information

See Boston, MA salary details

$15

$34

$56

How much do scientific machine learning jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for scientific machine learning in Boston, MA is $34.20, according to ZipRecruiter salary data. Most workers in this role earn between $20.91 and $43.61 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Boston, MA? For Scientific Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Boston, MA look for? The top searched job categories for Scientific Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Scientific Machine Learning jobs? Cities near Boston, MA with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Boston, MA as of August 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $71,130 per year, or $34.2 per hour.

Senior Scientist, Machine Learning

Flagship Pioneering

Cambridge, MA • On-site

$168 - $258.50/hr

Other

Medical, Retirement

Re-posted 24 days ago


Job description

What if…

you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologiesin order totransform health care and sustainability?

Flagship Labs 129 (FL129) is an early-stage biotechnology startup with an ambitious and exciting mission:to develop a technology tofacilitatethe data generation necessary for training the next generation of generative chemistry models to unlock the future of small molecule drug discovery. FL129 is developing a revolutionary approach to this challenge and is recruiting a team of top-tier scientists to build this powerful and first-in-category platform. This is a unique opportunity to be one of the first employees of a biotech startup that combines an innovative mindset with the resources andknow-howof Flagship Pioneering.

Position Summary:

We are seeking a motivated and highly collaborative Senior Scientist to join FL129’s growing team of experimental and computational scientists to build a novel platform technology. The successful candidate will have strong track record of scientific and technical innovation in machine learning for molecular modeling (proteins and/ small molecular ligands). Additional experience with computational docking methods is preferred. The ideal teammate will be highly adaptable, have strong organizational and communication skills, and will thrive in a highly collaborative and multidisciplinary environment.

Key Responsibilities:
  • Technology development , aligned with FL129’s core strategic goals. This role is among the first hires, andwe’relooking for someone who thinks critically and will influence the company’s scientific direction.
  • Development, training, validation, and application of novel generative chemistry andmolecular models
  • Curate training and benchmark datasets, and design and implement rigorous benchmarks to assess model performance.
  • Optimizeexisting workflows andestablishbest experimental and documentation practices to enable platform excellence.
  • Close collaboration with wet lab scientific team to drive achievement of key project goals.
  • Translate experimental data into meaningful insights and present results at team meetings.
Preferred Qualifications:
  • Ph.D. in machine learning, computational biology, or a similar field with 5+ years of industry or postdoctoral experience.
  • Familiarity with SOTA models such as Boltz-2, ESM-2, Chai-2 andrelated.
  • Experience training and fine-tuning molecular models for taskssuch as:protein language modeling, protein structure prediction, binder prediction, protein design, protein engineering, small molecule pose prediction, and related.
  • Experience curating publicly available datasets, including mutational scanning data.
  • Expertisewitha high-level programming language such as Python and modern HPC and cloud compute workflows.
  • Nice to have: Deep structural understanding of proteins.
  • Motivated team-player and independent force-of-nature with strong organizational and written/verbal communication skills.
What we can offer you:
  • Opportunity to lay the scientific foundation of a transformative platform company as an early employee.
  • Custom-tailored role to maximize impactful contributions, professional growth, and scientific interests.
  • Weekly lunches, monthly social events, and community lunchroom with free snacks, coffee, all embedded in a vibrant community of scientists and entrepreneurs across multiple Flagship Pioneering portfolio companies.

We are seeking individuals with an entrepreneurial spirit,strong communicationskills, and comfort in working in and contributing to a dynamic and cross-functional team environment. The level of the role will becommensuratewith the education and years of experience of the identified candidates.

Flagship Pioneering and our ecosystem companies are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, genderidentityor Veteran status.

Recruitment & Staffing Agencies

: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto

Privacy Notice for Applicants:

When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.

The salary range for this role is $168,000 - $258,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL129 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL129's good faith estimate as of the date of publication and may be modified in the future.

Privacy Notice for Applicants:

When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.

#J-18808-Ljbffr