- Provide technical leadership and guidance to the ML engineering team.
- Drive the design, development, and deployment of innovative ML solutions with a focus on efficiency, scalability, and maintainability.
- Break down complex problems into actionable steps and lead the development of effective algorithms and models.
- Champion best practices for software development, including clean code, version control, and documentation.
- Foster a collaborative learning environment and actively participate in knowledge sharing within the team.
- Possess 8+ years of experience in commercial software development with at least 3+ years dedicated to Machine Learning and AI.
- Demonstrate a strong understanding of machine learning principles, algorithms, and techniques (e.g., supervised learning, unsupervised learning, deep learning).
- Experience with building, training, and evaluating machine learning models using Python libraries like scikitlearn, TensorFlow, or PyTorch.
- Design and implement robust ML pipelines using tools and frameworks like Kubeflow, Seldon, or Spark.
- Containerize ML models using Docker for efficient deployment.
- Manage and orchestrate ML workloads on container orchestration platforms like Kubernetes (experience a plus).
- Collaborate with DevOps engineers to ensure seamless integration of ML models into production environments (experience with cloud services like AWS or Azure a plus).
- Excellent analytical and problemsolving skills.
- Strong communication and collaboration skills to work effectively with crossfunctional teams (technical and nontechnical).
- Ability to prioritize effectively, manage time efficiently, and deliver projects on schedule.
- Demonstrate a strong sense of ownership, urgency, and pride in your work.
- Proven ability to troubleshoot production issues and identify root 8+ years of experience in commercial software development.
- 3+ years of experience in Machine Learning and AI.
- Strong proficiency in Python and machine learning libraries.
- Experience with Docker and containerization principles.
- Experience with Kubernetes (a plus).
- Experience with Kubeflow, Seldon, or Spark (a plus).
- Experience with cloud services like AWS or Azure (a plus).
- Excellent problemsolving, analytical, and communication skills.
- Strong leadership qualities and the ability to mentor junior team members.
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Description
Skills- Machine learning, kuber flow, Kubernetes, python, docker, sparkMode of Work- Hybrid
Notice:
Immediate to 15 Leadership:
Machine Learning Expertise:
Productionization and Infrastructure:
General Skills: