[MGIT7U2Q] Scientific Computing / Research Engineering Expert — Engineering

ZettaMine Labs Pvt. Ltd.; India; Remote; INR 1,800,000 - 3,000,000; Full time

Job summary

ZettaMine Labs Pvt. Ltd. in India invites applications for a short-term Scientific Computing / Research Engineering Expert – Engineering role. Remote, full-time, 40 hours/week, immediate start, for an AI training and evaluation project across engineering domains.

Ph.D. or equivalent advanced experience required; strong skills in Python, C/C++, Julia, MATLAB/Octave, and Bash, plus Linux proficiency. Experience in modeling, numerical analysis, and reproducible workflows is essential.

Qualifications

• Strong scientific programming skills in Python, C/C++, Julia, MATLAB/Octave, Bash or another relevant language.
• Hands-on experience working in Linux or terminal-based environments.
• Experience with engineering simulation, modeling, numerical analysis, optimization, signal processing, control systems, or technical data analysis.
• Strong understanding of numerical methods, engineering units, physical constraints, boundary conditions, tolerances, convergence, stability, and technical validation.
• Ability to build, debug, and validate reproducible computational engineering workflows.
• Ability to design realistic, multi-step terminal tasks based on real-world engineering workflows.
• Ability to create engineering datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.
• Ability to develop expert solutions using relevant programming languages and engineering software.
• Ability to create automated tests and objective grading criteria to validate engineering correctness.
• Ability to debug solver, dependency, workflow, precision, and performance issues.

Responsibilities

• Design realistic, multi-step terminal tasks based on authentic engineering and scientific workflows.
• Translate real-world engineering workflows into reproducible computational tasks covering modeling, simulation, optimization, data processing, debugging, and technical validation.
• Create engineering datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.
• Develop expert solutions using Python, C/C++, Julia, MATLAB/Octave, Bash, or relevant engineering software.
• Build reproducible and containerized environments with appropriate engineering tools and pinned dependencies.
• Develop tasks involving simulation, numerical analysis, optimization, control systems, signal processing, finite-element concepts, CAD-related data, and engineering design.
• Work across Mechanical, Electrical, Chemical, Aerospace, Civil, Materials, Biomedical, Robotics, Control Systems, and Computational Design domains.
• Create automated tests and objective grading criteria to validate engineering correctness.
• Validate units, physical constraints, tolerances, convergence, stability, boundary conditions, and numerical behavior.
• Debug solver, dependency, workflow, precision, and performance issues.
• Clearly document assumptions, requirements, expected outputs, and edge cases.
• Develop challenging technical tasks that can be used to train and evaluate frontier AI agents.
• Ensure computational workflows are reproducible, technically accurate, and objectively verifiable.

Skills

Python

C/C++

Julia

MATLAB/Octave

Bash

Linux

Education

PhD or postdoctoral experience

Tools

OpenFOAM

CalculiX

FEniCS

ROS

LTspice

QEMU

Docker

Git

CI/CD

HPC environments

Job description

We are hiring Scientific Computing / Research Engineering Experts – Engineering for a short-term AI Training and Evaluation project in India.

Role: Scientific Computing / Research Engineering Expert — Engineering

Experience: Ph.D., Postdoctoral Experience, or equivalent advanced technical experience in Engineering

Mode: Remote

Engagement: Full-Time – 40 Hours/Week

Start: Immediate

Mandatory Eligibility Criteria

Technical Qualification:

• Strong scientific programming skills in Python, C/C++, Julia, MATLAB/Octave, Bash, or another relevant language.
• Hands-on experience working in Linux or terminal-based environments.
• Experience with engineering simulation, modeling, numerical analysis, optimization, signal processing, control systems, or technical data analysis.
• Strong understanding of numerical methods, engineering units, physical constraints, boundary conditions, tolerances, convergence, stability, and technical validation.
• Ability to build, debug, and validate reproducible computational engineering workflows.
• Ability to design realistic, multi-step terminal tasks based on real-world engineering and scientific workflows.
• Ability to create engineering datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.
• Ability to develop expert solutions using relevant programming languages and engineering software.
• Ability to create automated tests and objective grading criteria to validate engineering correctness.
• Ability to debug solver, dependency, workflow, precision, and performance issues.

Educational Qualification:

Mandatory: Ph.D., postdoctoral experience, or equivalent advanced technical experience in an Engineering discipline.

Preferred: Advanced expertise in one or more areas including Mechanical Engineering, Electrical Engineering, Chemical Engineering, Aerospace Engineering, Civil Engineering, Materials Engineering, Biomedical Engineering, Robotics, Control Systems, or Computational Design.

Availability :

• 4 hours of PST overlap per day
• Immediate availability preferred

Others:

• Personal laptop/desktop and stable high-speed internet.
• Strong written and verbal communication skills.
• Ability to work remotely for the duration of the project.
• Experience with scientific libraries such as NumPy, SciPy, pandas, matplotlib, SymPy, or PyTorch.
• Familiarity with engineering tools such as OpenFOAM, CalculiX, FEniCS, ROS, LTspice-compatible workflows, QEMU, or similar software.
• Experience with FEM, CFD, robotics, embedded systems, control systems, or digital twins is preferred.
• Familiarity with Docker, Git, CI/CD, automated testing, or HPC environments.
• Experience developing technical benchmarks, programming tasks, simulation-based evaluations, or automated graders.
• Experience evaluating AI coding or terminal agents or working in research software engineering.
• Publications, patents, open-source contributions, or industry experience involving computational engineering are an advantage.
• Strong technical documentation and communication skills.
• Ability to maintain high quality and incorporate reviewer feedback.

What You’ll Work On:

• Design realistic, multi-step terminal tasks based on authentic engineering and scientific workflows.
• Translate real-world engineering workflows into reproducible computational tasks covering modeling, simulation, optimization, data processing, debugging, and technical validation.
• Create engineering datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.
• Develop expert solutions using Python, C/C++, Julia, MATLAB/Octave, Bash, or relevant engineering software.
• Build reproducible and containerized environments with appropriate engineering tools and pinned dependencies.
• Develop tasks involving simulation, numerical analysis, optimization, control systems, signal processing, finite-element concepts, CAD-related data, and engineering design.
• Work across Mechanical, Electrical, Chemical, Aerospace, Civil, Materials, Biomedical, Robotics, Control Systems, and Computational Design domains.
• Create automated tests and objective grading criteria to validate engineering correctness.
• Validate units, physical constraints, tolerances, convergence, stability, boundary conditions, and numerical behavior.
• Debug solver, dependency, workflow, precision, and performance issues.
• Clearly document assumptions, requirements, expected outputs, and edge cases.
• Develop challenging technical tasks that can be used to train and evaluate frontier AI agents.
• Ensure computational workflows are reproducible, technically accurate, and objectively verifiable.