Senior Rust & Machine Learning Engineer – Optimization

We're Hiring: Rust + Machine Learning Engineer

We are looking for a hands-on engineer with strong expertise in Rust Programming and a solid understanding of Machine Learning (ML) and Machine Learning Engineering (MLE).

The role will focus on optimization, machine learning systems, and building high-performance solutions, where strong programming, algorithmic, and problem-solving skills are essential.

Key Responsibilities

• Design, develop, and optimize high-performance software using Rust.
• Build and productionize Machine Learning solutions and pipelines.
• Work on complex optimization problems using mathematical and computational techniques.
• Develop efficient algorithms for large-scale optimization and ML workloads.
• Implement ML models and integrate them into production systems.
• Work on model training, evaluation, deployment, monitoring, and optimization.
• Develop scalable and reliable Machine Learning Engineering (MLE) workflows.
• Profile and optimize code for performance, memory efficiency, and latency.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, and Product teams.
• Analyze complex technical problems and develop efficient, production-ready solutions.
• Contribute to architecture and design decisions for ML and optimization systems.

Required Skills

• Strong hands-on experience with Rust programming language.
• Good understanding of Machine Learning concepts and algorithms.
• Strong understanding of Machine Learning Engineering (MLE) practices.
• Experience building and deploying ML models in production environments.
• Strong knowledge of Data Structures and Algorithms.
• Strong programming and problem-solving skills.
• Good understanding of optimization techniques and algorithms.
• Experience with model training, validation, evaluation, and deployment.
• Experience with Python for ML/data science workflows is preferred.
• Good understanding of software engineering principles, testing, debugging, and Git.

Good to Have

• Experience with mathematical optimization, constraint optimization, or operations research.
• Experience with Linear Programming, Integer Programming, or Nonlinear Optimization.
• Knowledge of PyTorch, TensorFlow, scikit-learn, or JAX.
• Experience with ML serving and inference optimization.
• Experience with distributed computing or high-performance computing.
• Knowledge of CUDA/GPU programming is a plus.
• Experience with Docker, Kubernetes, and cloud platforms.
• Experience working on performance-critical or low-latency systems.
• Knowledge of Rust-based ML/AI libraries or inference systems is an advantage.