Job Description
We are seeking a visionary Lead AI/ML Architect to define the technological roadmap for our next-generation predictive platforms. As we look toward 2026, the future of technology isn't just about code—it's about intelligence at scale. You will be at the forefront of deploying generative AI and deep learning models that redefine user experiences.
In this pivotal role, you will not only write code but will architect the infrastructure that powers our enterprise solutions. You will lead a high-performing team of engineers and data scientists, driving innovation from the lab to production.
Why join us?
- Work on cutting-edge projects that set the standard for 2026.
- Competitive compensation and equity packages.
- Remote-first culture with access to world-class tech stacks.
Responsibilities
- Architect Scalable Infrastructure: Design and deploy robust machine learning pipelines and cloud-native architectures on AWS or GCP.
- Leadership & Mentorship: Lead a diverse team of data scientists and ML engineers, fostering a culture of innovation and technical excellence.
- Roadmap Strategy: Define the technical vision for AI integration, identifying trends in NLP, Computer Vision, and Generative AI.
- Model Optimization: Oversee the full lifecycle of ML models, from experimentation and training to deployment and continuous monitoring.
- Cross-Functional Collaboration: Partner with product managers and engineering leads to translate complex business requirements into technical specifications.
- Security & Compliance: Ensure all AI implementations adhere to strict data privacy and security standards (GDPR, SOC2).
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically in Machine Learning and Deep Learning.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, or Scikit-learn. Experience with Kubernetes and Docker is required.
- Cloud Mastery: Deep understanding of cloud platforms (AWS, Azure, or GCP) and serverless architectures.
- Leadership: Proven track record of leading engineering teams and managing complex technical projects.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.