Senior Applied Engineer

About PhysicsX

PhysicsX is a pioneering deep-tech company rooted in numerical physics and Formula One, dedicated to accelerating hardware innovation at software-speed. We develop an AI-driven simulation software suite that enables high-fidelity, multi-physics simulations applicable across engineering and manufacturing sectors such as Aerospace, Defense, Materials, Energy, Semiconductors, and Automotive.

Our Singapore-based research team focuses on creating physical foundation models in collaboration with customers and partners, aiming at revolutionary engineering domains.

Key Responsibilities

• Collaborate extensively with research scientists, simulation engineers, and clients to deliver AI models tailored to solving practical physics and engineering challenges.
• Design and develop scalable physical foundation models optimized for training on large-scale multi-GPU cloud infrastructures.
• Convert research prototypes into stable, efficient implementations, evaluating and improving architecture decisions to enhance scalability.
• Advocate for and select optimal libraries, frameworks, and tools to ensure project success.
• Lead research work-streams proportionate to seniority level.
• Communicate research outcomes and their practical impact effectively with teammates and customers.
• Bridge data science and software engineering to transform research insights into reusable libraries, tools, and end products.
• Encourage intellectual curiosity and drive among colleagues and mentees.

Candidate Requirements

• A strong passion for engineering machine learning solutions, particularly in deep learning and probabilistic methods, for scientific and engineering applications.
• Capability to independently scope and successfully execute projects spanning multiple domains.
• Exceptional analytical skills for diagnosing problems, identifying root causes, and proposing swift, effective remedies.
• Excellent teamwork and communication skills for collaboration with internal teams and external customers.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or related disciplines, accompanied by experience in scientific computing, high-performance computing with CPUs/GPUs, and parallelized or distributed training of large foundation models.
• Preferably over two years of industry experience involving data-driven environments, model scaling and optimization, cloud platforms like AWS/Azure/GCP, distributed computing frameworks (Spark, Dask), HPC frameworks (MPI, OpenMP, CUDA, Triton), Python machine learning frameworks (NumPy, SciPy, Pandas, PyTorch, JAX), C/C++ for scientific computing, software engineering best practices, containerization (Docker), orchestration (Kubernetes, Slurm), and systematic experimental pipelines.

What We Offer

• Opportunity to contribute to impactful AI-native engineering technologies that solve critical industry and societal problems.
• Join a diverse, high-caliber team that values collaboration, continuous learning, and high standards.
• A flat organizational structure encouraging idea meritocracy and openness to challenging status quo.
• A sustainable work-life balance with a hybrid onsite-work-from-home model facilitating both connection and flexibility.
• Commitment to diversity and inclusive hiring practices, actively encouraging applications from underrepresented groups and supporting gender diversity initiatives in STEM education.

Diversity and Inclusion Commitment

We uphold equal employment opportunity irrespective of gender, race, ethnicity, religion, disability, age, sexual orientation, or gender identity. Diversity data collection supports compliance with employment laws and remains confidential.