Architect & Design: Design and develop highly scalable, resilient, and performant backend services and APIs to serve machine learning models;
Build & Implement: Write clean, maintainable, and well-tested code in Java, C/C++, Python, or other relevant languages to bring AI-powered products to life;
Productionize AI/ML: Collaborate closely with Data Scientists and ML Engineers to productionize AI models. This includes building inference services, data pipelines, and the infrastructure for model training, deployment, and monitoring (MLOps);
Lead & Mentor: Lead technical projects from conception to completion. Mentor junior engineers, conduct code reviews, and champion best practices in software engineering across the team;
CI/CD & Automation: Own and improve our continuous integration and deployment pipelines to ensure rapid, reliable delivery of new features and models;
Performance Optimization: Identify and resolve performance bottlenecks in our systems, ensuring low-latency and high-throughput for our AI services;
Cross-Functional Collaboration: Work in an agile environment with product managers, designers, and other engineering teams to define requirements and deliver high-impact solutions.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience;
At least 3+ years of professional experience in software development, with a proven track record of shipping complex, scalable backend systems;
Expert-level proficiency in at least one modern programming language such as Python, Go, Java, or C++;
Strong understanding of software architecture, data structures, and algorithms;
Experience designing, building, and maintaining RESTful APIs and/or gRPC, WebSocket services;
Solid understanding of the machine learning lifecycle, from data ingestion and training to deployment and monitoring in a production environment;
Experienced in working with SQL databases (MySQL, PostgreSQL, …) and NoSQL databases (Redis, MongoDB, ...);
Good at logical thinking and problem-solving skills;
Be willing to learn new technologies and programming language;
Nice to have:
Experience in designing, building Realtime API using WebRTC and/or WebSocket;
Experience with containerization and orchestration technologies, particularly Docker and Kubernetes;
Proficiency with machine learning frameworks like TensorFlow, PyTorch, Scikit-learn, TensorRT, Triton Inference Server, OpenVINO, Mojo, etc;
Demonstrated experience leading projects and mentoring other engineers;
Experience in a specific AI domain such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems
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