Responsibilities:
Able to help the product team in developing AI-driven solutions that align with business objectives
Acts as an engineering leader and technical expert, providing guidance and expertise across projects
Develops detailed engineering plans for the engineering team, establishing clear timelines for tasks and projects
Responsible for hiring, training, and mentoring engineering staff, fostering skill development and cultivating a high-performance team culture.
Takes operational responsibility for the services owned by the engineering team, ensuring services are consistently running and meeting performance standards.
Is responsible for ensuring the quality of AI systems throughout their lifecycle by testing model performance, validating data quality, ensuring adherence to ethical standards, and monitoring post-deployment performance
Possesses strong engineering knowledge to identify, assess, and mitigate technical and operational risks, ensuring the project's long-term maintainability.
Requirements:
At least 4 years of experience in developing AI systems and products
Strong communication skills to effectively convey complex concepts
Exceptional problem-solving skills with a creative, critical approach to addressing real-time challenges
Proficient in Python programming.
Detailed knowledge of linear algebra, and statistics to support AI model development and evaluation
In-depth understanding of machine learning algorithms and frameworks such as PyTorch
Nice to Have:
Knowledge of various databases, including relational (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) with expertise in selecting the right database for specific use cases and optimizing performance.
Familiarity with big data technologies and frameworks, such as Hadoop, Spark, or Kafka, with the ability to process, analyze, and derive insights from large-scale datasets efficiently.
Experience with containerization and orchestration tools like Docker and Kubernetes for deploying and managing AI systems at scale.