
AI Machine Learning Engineer
2 days ago
We are seeking a highly skilled Senior AI Engineer to join our team. The ideal candidate will have extensive experience in machine learning and natural language processing, with a strong background in software development.
The successful candidate will be responsible for designing and developing AI/ML solutions, leveraging cloud platforms such as AWS, and leading a team of data scientists and machine learning engineers on complex projects.
- Key Responsibilities:
- Develop and implement machine learning models and algorithms, including supervised, unsupervised, deep learning, and reinforcement learning techniques.
- Implement Generative AI solutions using technologies like RAG (Retrieval-Augmented Generation), Vector DBs, and frameworks such as LangChain and Hugging Face, Agentic AI.
- Utilize popular AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn.
- Design and deploy NLP models and techniques, including text classification, RNNs, CNNs, and Transformer-based models like BERT.
- Ensure robust end-to-end AI/ML solutions, from data preprocessing and feature engineering to model deployment and monitoring.
- Demonstrate strong programming skills in languages commonly used for data science and ML, particularly Python.
- Leverage cloud platforms and services for AI/ML, especially AWS, with knowledge of AWS Sagemaker, Lambda, DynamoDB, S3, and other AWS resources.
- Mentor and coach a team of data scientists and machine learning engineers, fostering skill development and professional growth.
- Provide technical guidance and support, helping team members overcome challenges and achieve project goals.
- Set technical direction and strategy for AI/ML projects, ensuring alignment with business goals and objectives.
- Facilitate knowledge sharing and collaboration within the team, promoting best practices and continuous learning.
- Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and products.
- Provide strategic insights and recommendations to support decision-making processes.
- Communicate effectively with stakeholders at various levels, including technical and non-technical audiences.
- Extensive proficiency with generative AI technologies, including RAG, Vector DBs, and frameworks such as LangChain and Hugging Face, Agentic AI.
- Proficiency in machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- Extensive proficiency with AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn.
- Strong knowledge of natural language processing (NLP) techniques and models, including Transformer-based models like BERT.
- Proficient programming skills in Python.
- Proficiency with cloud platforms like AWS, including AWS Sagemaker, Lambda, DynamoDB, S3, and other AWS resources.
- Proven ability to lead a team of data scientists or machine learning engineers on complex projects.
- Strong project management skills, with the ability to prioritize tasks, allocate resources, and meet deadlines.
- Excellent communication skills and the ability to convey complex technical concepts to diverse audiences.
- Strong problem-solving and analytical abilities.
- Proven ability to manage projects and activities.
- Proficiency in setting technical direction and strategy for AI/ML projects.
- Knowledge of the Insurance domain.
- Ability to mentor and coach junior team members, fostering growth and development.
- Proven track record of successfully managing AI/ML projects from conception to deployment.
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