Machine Learning Engineer - Core

【About the Role】
As a Machine Learning Engineer specializing in Core Pipeline development, you will help turn machine learning ideas into reliable systems used in real production environments.
Core Pipeline Engineers form the foundation of our machine learning engineering organization. This is a broad engineering role for someone who enjoys working across algorithms, software systems, data pipelines, model training/inference services. You will grow with the product, develop deeper ownership over time, and adapt your work as its technical and operational needs evolve.
We build products that integrate directly into production workflows and deliver measurable impact on the production floor. You will work closely with data scientists, machine learning engineers, and deployment teams to bring solutions toward production deployment and sustain them through long-term operation.

【Responsibilities】

• Design, build, deploy, and maintain production machine learning systems across the machine learning lifecycle, transforming algorithms and experimental implementations into reliable and maintainable software.
• Investigate and resolve issues involving data pipelines, runtime performance, system integration, and production reliability.
• Take ownership of key product components and collaborate with data scientists, machine learning engineers, and forward-deployment engineers to adapt solutions as product and production needs evolve.
• Follow and promote good engineering practices by writing clean and testable code, participating in code reviews, maintaining clear technical documentation, and evaluating relevant engineering trade-offs.

【Key Qualifications】

• Strong programming and software engineering fundamentals, with proficiency in Python, C++, C, or other relevant programming languages and the ability to learn the tools required by the project.
• A solid understanding of the end-to-end machine learning lifecycle and basic machine learning evaluation metrics, with experience developing machine learning and deep learning systems using PyTorch, as well as tools such as NumPy, Pandas, and scikit-learn.
• Familiarity with Git-based development workflows and CI/CD practices.
• Strong problem-solving, communication, and collaboration skills, with an interest in developing meaningful ownership of a product.

【Preferred, but Not Required】

• Experience with computer vision, image processing, or related applications. Candidates with experience in other machine learning domains are also welcome.
• Experience moving machine learning systems from experimentation into reliable operation in production.
• Familiarity with databases, caches, and messaging/streaming pipelines, including technologies such as SQLite, Redis, RabbitMQ, or similar tools.
• Understanding of parallel and concurrent programming concepts, including multithreading, multiprocessing, asynchronous programming, and GPU-accelerated workloads.
• Familiarity with containers, orchestration, monitoring, and observability using technologies such as Docker, Kubernetes, Prometheus.
• Experience reasoning about runtime, memory, synchronization, data transfer, and I/O trade-offs in performance-sensitive, data-intensive, or high-performance computing systems.
• Experience with data pipelines, ETL workflows, workflow orchestration with tools such as Apache Airflow.

You do not need to match every preferred qualification. We value strong engineering fundamentals, practical problem-solving skills, and the ability to learn and grow with the product. We are hiring for both mid-level and senior-level engineering positions, and the scope and expectations of the role will be considered based on your experience and seniority during the interview process.