Description
We are seeking a highly experienced
Lead AI Engineer to design and develop complex AI projects, and lead a team of talented AI Engineers at DataFlow Group.
This role is a combination of hands-on engineering, technical design, and development. The Lead AI Engineer will be responsible for defining the Model experiments, evaluating the architecture, ensuring the technical quality of all AI products, and fostering a culture of innovation.
Responsibilities
- Research and evaluate new Models and determine their applicability to business problems.
- Lead the design and implementation of highly scalable, reliable, and secure AI systems in production.
- Proven ability to apply sophisticated ML skills, including advanced feature engineering, ensemble methods, deep learning architectures, and statistical modeling.
- Provide technical solutions, and guide the Junior and Senior engineers towards delivering the solution.
- Demonstrated experience in applied research, resulting in improvements to model accuracy, efficiency, or novel solution development.
- Oversee code quality, model governance, and adherence to MLOps best practices across all projects.
- Work closely with cross functional teams to translate research prototypes into robust, deliverable products.
Minimum Qualifications
- Master's or Ph.D. in Computer Science, AI, or a related technical field.
- 7+ years of progressive professional experience in AI/ML engineering, with at least 2 years in a lead engineer role.
- Demonstrated expertise in designing and managing end-to-end MLOps architectures at scale.
- Deep architectural knowledge of cloud-native ML services and infrastructure (Advanced proficiency in one or more major cloud providers: AWS, GCP, or Azure).
- Proven track record of successfully deploying and maintaining multiple high-impact AI systems in a commercial environment.
- Exceptional system design skills, including API design, microservices, and distributed computing.
- Strong leadership, communication, and collaboration skills with the ability to influence technical direction.
Preferred Qualifications
- Deep domain expertise in a specific area (e.g., Generative AI, Large Language Models (LLMs), Reinforcement Learning).
- Contributions to open-source ML projects or relevant publications.
- Familiarity with big data technologies (e.g., Spark, Hadoop).
(ref:hirist.tech)
