Design, develop, and deploy machine learning models and AI solutions that address real-world customer problems, focusing on usability, scalability, and performance.
Rapidly develop demos, POCs, MVPs, and workflows to showcase new AI/ML capabilities that could be integrated into the product or used to improve existing features based on customer feedback or market research.
Develop and improve integrations of open-source ML/AI tools (e.g., MLFlow, Spark, LangChain, Kubeflow) within production environments, ensuring seamless operation on platforms like Kubernetes.
Fine-tune models and algorithms for accuracy, efficiency, and scalability in production settings, including deep learning technologies.
Translate customer requirements and industry trends into actionable AI/ML solutions that improve product features, data management, and system performance.
Work closely with product managers, data scientists, and engineering teams to brainstorm, design, and deploy AI/ML solutions, documenting procedures and best practices.
Lead efforts in integrating emerging AI tools, mentor junior team members, and communicate progress and challenges to leadership.

PhD with at least 2 years of relevant industry experience, or the equivalent (e.g., Master’s degree with 4+ years, Bachelor's with 6+ years)
Extensive hands-on experience applying machine learning and AI solutions in customer-facing or end-user environments.
Proven ability to deploy models in production, ensuring reliability and performance.
Experience with open-source ML/AI tools and frameworks.
Experience with backend programming languages (Python, Go).
Proficiency in developing, using, and maintaining AI agents; proven experience coding agents for automation or decision-making tasks.
Excellent written and verbal communication skills, especially in asynchronous collaboration.

Senior Applied Machine Learning Engineer

Key skills