Machine Learning Software Engineer, Research

About The Company

PhysicsX is a pioneering deep-tech company rooted in numerical physics and inspired by the high-performance environment of Formula One racing. Our mission is to accelerate hardware innovation by integrating advanced AI-driven simulation software into engineering and manufacturing processes across various high-tech industries. We focus on delivering high-fidelity, multi-physics simulations through AI inference, enabling comprehensive analysis throughout the entire engineering lifecycle. Our innovative solutions unlock new possibilities for optimization and automation in design, manufacturing, and operational workflows. Serving leading organizations in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive sectors, PhysicsX is committed to pushing the boundaries of technological advancement and scientific discovery.

About The Role

We are seeking a talented and enthusiastic Machine Learning Software Engineer, Research to join our dynamic team. In this role, you will collaborate closely with research scientists and simulation engineers to develop, optimize, and deploy machine learning models that solve complex physics and engineering challenges. Your work will involve designing scalable ML architectures, transforming prototypes into robust production systems, and exploring distributed training techniques across cloud and on-premise environments. You will play a key role in building foundation models for scientific applications, ensuring that our models are efficient, scalable, and capable of handling large datasets and multi-GPU training. The ideal candidate will have a passion for scientific computing, deep learning, and innovative problem-solving, with the ability to work independently and contribute to a collaborative research environment.

Qualifications

• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or related fields
• Experience in scientific computing, high-performance computing (CPU/GPU clusters), and parallel/distributed training
• At least 1 year of experience in a data-driven role involving ML model scaling, optimization, and deployment
• Proficiency with distributed computing frameworks such as Spark or Dask
• Experience with cloud platforms like AWS, Azure, or GCP
• Strong programming skills in Python, with familiarity in libraries such as NumPy, SciPy, Pandas, PyTorch, and JAX
• Knowledge of C/C++ for computer vision, geometry processing, or scientific computing applications
• Understanding of software engineering best practices including version control, testing, CI/CD, and API design
• Experience with containerization and orchestration tools such as Docker and Kubernetes
• Familiarity with MLOps principles and building systematic experiment pipelines
  
  

Responsibilities

• Collaborate with research scientists and engineers to develop models addressing real-world physics and engineering problems
• Design, build, and optimize machine learning models focusing on scalability and computational efficiency
• Transform prototype models into production-ready, optimized implementations
• Implement distributed training architectures for multi-node and multi-GPU environments, including exploring federated learning capabilities
• Scale and optimize foundation models for scientific and engineering applications, managing large datasets and cloud-based compute resources
• Select appropriate libraries, frameworks, and tools to enhance modeling efforts and ensure project success
• Lead or contribute to research work streams, mentoring less experienced colleagues as needed
• Communicate research findings and model implications effectively to internal teams and external clients
• Translate research outcomes into reusable software libraries, tools, and products that can be integrated into our simulation platform
  
  

Benefits

• Equity options providing ownership stake in the company's growth
• 5% 401(k) match to support your financial future
• Flexible working arrangements to promote work-life balance
• Hybrid work setup with access to our Manhattan office and remote work flexibility
• Enhanced parental leave to support major life milestones
• Comprehensive private healthcare coverage for you and your family
• Access to continuous learning and professional development opportunities
• Work-from-anywhere options to enjoy a flexible and comfortable working environment
  
  

Equal Opportunity

PhysicsX is committed to fostering an inclusive and diverse workplace. We provide equal employment opportunities regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation, or gender identity. We actively encourage applications from underrepresented groups in technology and support initiatives such as sponsorship programs for women from disadvantaged backgrounds pursuing degrees in science and mathematics.