What you'll be doing

• Collaborate with teams to research, scope, and validate use cases for AI that drive business value and innovation.
• Drive AI adoption by combining rigorous scientific evaluation with operational maturity to champion high-value applications and push back on unsuitable use cases.
• Design, refine, and build MLOps components of the data and AI platform, including Vector Databases, feature stores, and model serving at millisecond scale.
• Implement CI/CD pipelines and ensure best practices for model deployment, security, and compliance with global regulations.
• Participate in the AI/ML guild to influence new approaches and use cases.
• Continuously monitor and optimize system performance to ensure scalability, security, and operational efficiency.

Requirements

• Proficiency in Python and at least one other programming language is a plus.
• Experience with AI libraries such as PyTorch, Pandas, Hugging Face Transformers, or similar toolkits.
• Working knowledge of common AI models, their use cases, and practical application to problem-solving.
• Strong engineering skills in designing and implementing services, data models, and features.
• Expertise with cloud computing platforms like AWS, GCP, or Azure, and containerization tools such as Docker and Kubernetes.
• Experience with modern data platforms (e.g., BigQuery, Databricks) and data processing workflows (ETL, pipelines).
• Excellent experience with cloud-hosted AI platforms such as Bedrock, SageMaker, or VertexAI.
• Strong problem-solving abilities and ability to adapt quickly in a fast-paced environment.
• Excellent communication skills and a drive to work effectively across diverse teams.

Nice to haves

• Experience developing AI/ML applications, including fine-tuning models or creating prototypes.
• Awareness of ethical considerations and emerging best practices in AI governance.
• Track record for rapid prototyping and bringing solutions to production with a focus on measurable ROI.
• Familiarity with distributed systems and large-scale data processing.
• Contributions to open-source projects or a strong GitHub portfolio.
• Thought leadership demonstrated through articles or speaking engagements.
• High levels of technical curiosity and eagerness to learn new platforms.

Perks and benefits

• Hybrid working model with office onsite 3 times per week (Tuesday, Wednesday, and Friday).
• Collaborative work environment with global team partnerships.
• Complimentary snacks, breakfast, and lunch options at all office locations.
• Supportive culture focused on real ownership, fewer blockers, and impactful work from day one.
• Commitment to accessibility and inclusivity in the workplace and recruitment process.