The Senior AI Engineer is a senior individual contributor with deep expertise in a specific domain of AI/ML, responsible for tackling the most complex technical challenges, driving architectural decisions for critical AI components, and setting technical standards.
This role requires a blend of advanced research understanding and robust engineering skills to bring cutting-edge AI innovations into production.
The difference you will make Act as a subject matter expert in one or more specialized AI/ML domains (e.
g., Generative AI, Explainable AI, Large Language Models, Reinforcement Learning, Real-time Anomaly Detection).
Lead the design and implementation of highly scalable, fault-tolerant, and high-performance AI systems and infrastructure.
Evaluate and integrate new AI/ML research, algorithms, and technologies into product development.
Drive continuous improvement in MLOps, model monitoring, and model governance frameworks.
Provide expert technical guidance and mentorship to other AI Engineer 1s and Associates.
Conduct complex performance tuning, optimization, and debugging of AI/ML models and pipelines.
Participate in strategic planning for AI initiatives, identifying opportunities for technological advancement.
Influence technical direction and architecture discussions within the AI/ML team and across engineering.
Lead code reviews for critical components, ensuring architectural integrity, performance, and maintainability.
Education: Bachelor’s degree or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.
Experience: 5+ years of progressive experience in AI/ML engineering, with a proven track record of designing and deploying complex AI systems into production.
Demonstrated deep expertise in a specific AI sub-field.
Technical Skills: Expert-level proficiency in Python and advanced ML/DL frameworks (e.
g., PyTorch, TensorFlow, JAX).
Extensive experience with cloud-native AI/ML services and distributed computing frameworks (e.
g., Spark, Ray).
Deep understanding and hands-on experience with MLOps best practices, including CI/CD, model serving, and monitoring in production environments.
Strong architectural design skills for complex data pipelines and scalable AI inference systems.
Proficiency in system design, distributed systems, and performance optimization.
Ability to critically evaluate and apply academic research to real-world problems.
Soft Skills: Strong ownership and accountability for assigned work.
Clear and professional verbal and written communication.
Effective time management and task prioritization.
o Analytical thinking and problem-solving skills.
Ability to work independently, collaborate effectively and mentor junior team members.
Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
Adaptability and learning agility in a fast-paced environment.
Strong attention to detail and a commitment to quality.
Receptiveness to feedback and continuous improvement mindset Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment.
All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.
