Job Description
Are you ready to define the next era of artificial intelligence? Vertex AI Solutions is seeking a visionary Senior AI/ML Engineer to join our elite R&D team. We are building the infrastructure that powers the future of autonomous systems and generative AI. In this role, you will not just write code; you will architect the neural networks that will define how machines understand and interact with the world.
Our mission is to democratize advanced intelligence. We work with cutting-edge hardware and cloud-native architectures to deliver scalable, high-performance models. If you thrive in a fast-paced, innovative environment and are passionate about pushing the boundaries of what's possible in Machine Learning, we want to hear from you.
Why Join Us?
- Competitive salary and equity package.
- Top-tier health, dental, and vision insurance.
- Unlimited PTO and flexible remote-first work policy.
- Access to the latest GPUs and cloud resources for research.
Responsibilities
- Architecture & Development: Design, develop, and deploy scalable machine learning models and deep learning pipelines using Python, PyTorch, and TensorFlow.
- Research & Innovation: Conduct cutting-edge research to improve model accuracy, efficiency, and robustness for our core products.
- Infrastructure: Implement MLOps best practices, including CI/CD pipelines, model versioning, and automated testing to ensure production-grade reliability.
- Collaboration: Partner with cross-functional teams of data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Optimization: Optimize existing models for speed, memory usage, and inference latency in real-time environments.
- mentoring: Mentor junior engineers and guide them through complex technical challenges.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering or applied research.
- Programming: Strong proficiency in Python, with deep knowledge of PyTorch or TensorFlow.
- Tools: Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Data: Proficiency in SQL and experience working with large-scale datasets (Spark, Hadoop).
- Soft Skills: Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.