Deskripsi Pekerjaan
At Nexus AI Labs, we are building the next generation of intelligent systems that transform how enterprises leverage data. We are seeking a Senior Machine Learning Engineer to lead the design, development, and deployment of scalable ML models that power our core products. You will work at the intersection of research and engineering, collaborating with a world-class team to solve complex, high-impact problems in natural language processing, computer vision, and predictive analytics.
This is a high-autonomy role for a builder who thrives in a fast-paced, innovative environment. You will own the full ML lifecycle—from data strategy and model architecture to production monitoring and optimization. If you are passionate about pushing the boundaries of applied AI and delivering tangible business value, we want to hear from you.
Tanggung Jawab
- Design, train, and optimize state-of-the-art machine learning models (LLMs, Transformers, CNNs) for production-scale deployment.
- Architect robust, scalable ML pipelines for data ingestion, feature engineering, training, evaluation, and automated retraining (CI/CD for ML).
- Collaborate with Product and Data Engineering to define model requirements, success metrics, and data acquisition strategies.
- Conduct rigorous offline/online experimentation (A/B testing) to validate model improvements and measure business impact.
- Implement model monitoring, drift detection, and observability frameworks to ensure reliability in production.
- Mentor junior engineers, establish best practices for MLOps, and contribute to the technical roadmap.
- Stay current with latest research (NeurIPS, ICML, ICLR) and prototype novel techniques for domain-specific challenges.
- Optimize model inference latency and cost through quantization, distillation, and hardware acceleration (GPU/TPU).
Kualifikasi
- M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or equivalent practical experience.
- 5+ years of industry experience building and deploying ML models at scale in a production environment.
- Expert proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX, Hugging Face).
- Deep understanding of ML theory: optimization, generalization, deep learning architectures, and probabilistic modeling.
- Strong MLOps background: Docker, Kubernetes, Kubeflow/MLflow, Airflow, and cloud platforms (AWS/GCP/Azure).
- Proven track record of shipping NLP, CV, or Recommender Systems projects from ideation to live traffic.
- Excellent software engineering skills: clean code, design patterns, testing, version control (Git), and code review practices.
- Ability to communicate complex technical concepts to both technical and non-technical stakeholders.