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Scientific Machine Learning Jobs in Valley Stream, NY

NxT Level

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

A degree in Computer Science, Machine Learning, or a related field, or equivalent professional experience. * A strong theoretical foundation in core Machine Learning concepts and techniques.

NxT Level

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

A degree in Computer Science, Machine Learning, or a related field, or equivalent professional experience. * A strong theoretical foundation in core Machine Learning concepts and techniques.

PhysicsX

Machine Learning Engineer

New York, NY · On-site

Working at the intersection of data science and software engineering, you translate R&D and project ... This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation ...

Point72

Machine Learning Engineer

Manhattan, NY · On-site

PhD or PhD candidate in machine learning, computer science or other AI related research fields * Experience with sequential modeling and time series forecasting using deep learning * Experience with ...

Point72

Machine Learning Engineer

New York, NY · On-site

PhD or PhD candidate in machine learning, computer science or other AI related research fields * Experience with sequential modeling and time series forecasting using deep learning * Experience with ...

Point72

Machine Learning Engineer

New York, NY

PhD or PhD candidate in machine learning, computer science or other AI related research fields * Experience with sequential modeling and time series forecasting using deep learning * Experience with ...

ExaCare AI

Machine Learning Engineer

Manhattan, NY · On-site

$110 - $150/hr

We are seeking a highly adaptable, creative, and well‑rounded Machine Learning Engineer to join ... Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related technical field.

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Scientific Machine Learning information

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How much do scientific machine learning jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for scientific machine learning in Valley Stream, NY is $32.93, according to ZipRecruiter salary data. Most workers in this role earn between $20.10 and $42.02 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 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 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 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 job categories do people searching Scientific Machine Learning jobs in Valley Stream, NY look for?

The top searched job categories for Scientific Machine Learning jobs in Valley Stream, NY are:

What cities near Valley Stream, NY are hiring for Scientific Machine Learning jobs?

Cities near Valley Stream, NY with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you

Machine Learning Scientist/Senior Machine Learning Scientist - Synthesis Planning and Optimization,

Genentech

Manhattan, NY • On-site

$100K - $137K/yr

Full-time

Re-posted 28 days ago

Genentech rating

8.8

Company rating: 8.8 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

11th of 86 rated pharmaceutical

Job description

Job Summary:
Genentech is a company dedicated to innovating healthcare for a healthier future. They are seeking a Machine Learning Scientist / Senior Machine Learning Scientist to develop machine learning methods for synthesis-aware molecular design to assist scientists in drug discovery.
Responsibilities:
• Develop and advance machine learning methods for synthesis-aware molecular design across retrosynthesis, synthesis planning, molecular generation, and search in synthesizable chemical spaces.
• Integrate proprietary reaction and biochemical data to design the next generation of synthesis-aware models and workflows for hit finding and optimisation.
• Build robust, scalable pipelines for active-learning loops that interface directly with automated and high-throughput synthesis platforms.
• Design novel batch synthesis-planning algorithms that maximise chemical-space coverage, information gain and experimental efficiency.
• Drive scientific impact through publications, open-source releases, and conference talks.
• Collaborate widely with computational and experimental researchers at Roche and with academic partners.
Qualifications:
Required:
• Deep machine-learning expertise with a strong foundation in linear algebra, probability and optimization.
• Hands-on experience in modern machine learning approaches such as graph-neural networks, sequence/language models and reinforcement learning.
• Familiarity with chemistry concepts relevant to synthesis planning and molecular optimisation.
• Experience with small molecule data and cheminformatics toolkits such as RDKit or Openeye.
• Fluency in Python.
• Experience with modern ML frameworks like PyTorch or JAX.
• Experience with scientific software development.
• PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering or a related quantitative field such as physics or statistics.
• Up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).
• Record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects (e.g. hosted on GitHub/GitLab).
Preferred:
• Experience with retrosynthesis or synthesis-planning models.
• Experience with automated/high-throughput synthesis.
Company:
Genentech is a biotechnology research company that specializes in genetic testing and personalized medicines. Founded in 1976, the company is headquartered in South San Francisco, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Genentech employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Genentech

Sourced by ZipRecruiter

A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.

Industry

Scientific research and development services

Company size

10,000+ Employees

Headquarters location

South San Francisco, CA, US

Year founded

1976

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