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Machine Learning Cfd Jobs in Manhattan, NY (NOW HIRING)

PhysicsX

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Who We're Looking For As a Senior Machine Learning Engineer in Delivery, you are an experienced ... Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data ...

PhysicsX

Principal CFD Engineer

New York, NY · On-site

You're confident setting up CFD simulations independently, interpreting complex results with depth ... This Role In this role, you'll work closely with our Data Scientists, Machine Learning Engineers ...

All JobsMachine Learning Cfd JobsMachine Learning Cfd Jobs in Manhattan, NY

Machine Learning Cfd information

See Manhattan, NY salary details

$12.1K

$102.7K

$145.7K

How much do machine learning cfd jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning cfd in Manhattan, NY is $102,653.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,400.00 and $121,400.00 per year, depending on experience, location, and employer.

What is a machine learning CFD?

Machine Learning CFD (Computational Fluid Dynamics) jobs focus on integrating machine learning techniques with traditional fluid dynamics simulations and analyses. Professionals in this field use AI and data-driven models to accelerate simulations, improve prediction accuracy, and optimize fluid flow processes. These roles often require knowledge of both CFD principles and machine learning algorithms, and are commonly found in industries such as aerospace, automotive, and energy. Typical responsibilities include developing surrogate models for simulations, automating data analysis, and implementing deep learning approaches for complex flow problems.

How does a machine learning CFD professional typically collaborate with domain experts and software engineers in a project setting?

As a Machine Learning CFD (Computational Fluid Dynamics) professional, you’ll frequently collaborate with domain experts such as mechanical or aerospace engineers to ensure your models accurately reflect physical phenomena. You’ll also work closely with software engineers to integrate machine learning algorithms into simulation pipelines and optimize computational performance. Effective communication is key, as you’ll need to translate complex data-driven insights into actionable engineering solutions and vice versa. These collaborative efforts help streamline workflows, improve model accuracy, and ensure practical deployment of ML-enhanced CFD tools.

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

AspectMachine Learning CFDData Scientist
Required CredentialsDegree in Engineering, Computer Science, or related fields; knowledge of CFD softwareDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentEngineering firms, aerospace, automotive industries, research labsBusiness, finance, tech companies, research institutions
Industry UsageSimulation, fluid dynamics, engineering analysisData analysis, predictive modeling, business insights

Machine Learning CFD focuses on applying machine learning techniques to computational fluid dynamics simulations, often within engineering contexts. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming skills and a strong analytical background, Machine Learning CFD emphasizes simulation and engineering applications, whereas Data Scientists focus on data-driven decision-making across diverse sectors.

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

To thrive as a Machine Learning CFD Engineer, you need a strong background in fluid dynamics, numerical methods, and machine learning, often supported by a degree in engineering, physics, or computer science. Familiarity with CFD software (such as ANSYS Fluent or OpenFOAM), programming languages like Python or C++, and machine learning frameworks (TensorFlow or PyTorch) is essential. Critical thinking, problem-solving, and effective communication are standout soft skills for interpreting data and collaborating on interdisciplinary teams. These competencies are crucial for developing innovative solutions that enhance simulation accuracy and computational efficiency in engineering projects.
What are popular job titles related to Machine Learning Cfd jobs in Manhattan, NY? For Machine Learning Cfd jobs in Manhattan, NY, the most frequently searched job titles are:
What job categories do people searching Machine Learning Cfd jobs in Manhattan, NY look for? The top searched job categories for Machine Learning Cfd jobs in Manhattan, NY are:
What cities near Manhattan, NY are hiring for Machine Learning Cfd jobs? Cities near Manhattan, NY with the most Machine Learning Cfd job openings:
Machine Learning Cfd jobs near you
Infographic showing various Machine Learning Cfd job openings in Manhattan, NY as of June 2026, with employment types broken down into 13% As Needed, 44% Full Time, 16% Part Time, 9% Temporary, 9% Contract, and 9% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $102,653 per year, or $49.4 per hour.

Senior Machine Learning Engineer

PhysicsX

New York, NY • On-site

$114K - $157K/yr

Full-time

Retirement, PTO

Re-posted 18 days ago

Job description

About us
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
Who We're Looking For
As a Senior Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
Note: This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.
This Role
As a Senior MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.
You'll:
  • Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization & control) to customer production environments.
  • Communicate results and trade-offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
  • Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
  • Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
  • Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision-making under pressure.
  • Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
  • Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.

As a senior member of the team, you'll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you'll contribute to this exciting journey!
What we offer
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesn't stop there ...
Equity options - share meaningfully in the company you're helping to build.
5% contribution to 401(k) - build long-term security with a strong retirement plan.
Free team lunch 1x/week - good food, great company, and space to connect.
Private health insurance - comprehensive cover for you, offering total peace of mind.
Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
Personal development - dedicated support for learning, development, and leveling up over time.
Gympass / Wellhub (subsidized) - for you and up to 3 family members, supporting both physical and mental wellbeing.
Flexible Spending Account (FSA) - set aside pre-tax dollars for eligible healthcare expenses.
Watch this space, we're continuing to build this as we grow...
Salary range:
$200,000 - $250,000 depending on experience
Seniority will be assessed throughout our interview process
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

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