Job Description
We are looking for a visionary Senior AI & Machine Learning Engineer to lead the technical architecture for our next-generation intelligence systems. As we prepare for the future, this role is pivotal in defining our 2026 AI roadmap, focusing on Large Language Models (LLMs), autonomous agents, and ethical AI deployment.
In this role, you will not just implement existing solutions; you will architect the foundational technologies that will power our products for years to come. You will thrive in a high-performance environment that values innovation, scalability, and technical excellence.
Why Join Us?
- Work on cutting-edge AI projects that define the future of technology.
- Competitive compensation package with equity options.
- Flexible remote and hybrid work policies.
Responsibilities
- Architect Scalable Systems: Design and implement robust machine learning pipelines and infrastructure using Python, TensorFlow, and PyTorch.
- Model Development: Lead the research and development of deep learning models, including computer vision and natural language processing (NLP) applications.
- Production Optimization: Optimize model inference latency and accuracy in high-traffic production environments.
- Strategic Roadmap: Define the technical strategy for our 2026 AI initiatives, staying ahead of industry trends and emerging technologies.
- Collaboration: Partner with product managers and data scientists to translate complex business requirements into elegant technical solutions.
- MLOps Implementation: Establish CI/CD pipelines and automated testing frameworks to ensure reliable model deployment.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in AI/ML engineering, data science, or a related role.
- Programming: Proficiency in Python, SQL, and deep learning frameworks (TensorFlow, PyTorch, Keras).
- Cloud & DevOps: Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Advanced Knowledge: Strong understanding of MLOps, data engineering, and model evaluation techniques.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.