AI Architect
Noida · Staff/Principal
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Job description
About Us
Role Overview
Key Responsibilities
- Define the AI architecture and strategy aligned with product and business goals.
- Design scalable ML/AI models and workflows for platform intelligence, automation, user behavior analytics, risk detection, and personalization.
- Integrate Talosafe features and APIs into our platform; extend Talosafe modules where required.
- Lead the selection and deployment of AI tools, data pipelines, and model lifecycle practices (MLOps).
- Collaborate with cross-functional teams to align AI design with security, privacy, compliance, and performance.
- Provide thought leadership on ethical AI practices, explainable AI (XAI), and responsible data use.
- Build and guide a high-performing team of ML engineers and data scientists.
Required Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, or related field. PhD is a plus.
- 10+ years of software development/architecture experience; 5+ in AI/ML.
- Proven experience deploying production-grade AI/ML systems at scale.
- Hands-on experience with PV safety intelligence, especially in areas like:
- Safety and risk intelligence modeling
- Anomaly detection or behavioral AI
- Integration with SaaS compliance modules
- Proficient in Python, TensorFlow/PyTorch, MLflow, Spark/Databricks, Kubernetes.
- Familiarity with cloud-native AI tools (AWS SageMaker, Azure ML, or GCP Vertex AI).
- Strong understanding of data privacy regulations (GDPR, HIPAA) and secure AI practices.
Preferred Skills
- Experience working in platform-centric SaaS environments.
- Familiarity with product-led AI development.
- Exposure to CI/CD pipelines for ML (MLOps) and model governance.
- Published work, patents, or open-source contributions in AI/ML is a bonus.
Why Join Us?
- Opportunity to architect the AI backbone of a cutting-edge SaaS platform.
- Collaborative, open culture with a focus on innovation and speed.
- Work with a passionate team solving real-world safety and intelligence challenges.
- Competitive compensation, ESOPs, and learning opportunity
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