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AI/ML Engineer
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We are seeking a highly skilled Advanced AI/ML Engineer to drive innovation and excellence in our AI and machine learning endeavors. This role is instrumental in developing and deploying cutting-edge AI systems that enhance software and hardware products. You will be at the forefront of prototyping new ideas, collaborating with cross-functional teams, and transforming concepts into production-level solutions.
Key Responsibilities:
- Design and implement comprehensive AI systems and frameworks, ensuring their scalability and robustness.
- Maintain AI systems in production to ensure ongoing accuracy and reliability.
- Develop proofs of concept and prototypes, focusing on algorithm feasibility and model performance.
- Explore and apply state-of-the-art data science techniques for advanced modeling and algorithm development.
- Lead and manage end-to-end projects involving both structured and unstructured data.
- Mentor junior team members, sharing expertise in AI/ML best practices and methodologies.
- Oversee multiple projects, ensuring timely and successful completion.
- Create sophisticated data visualizations and dashboards for effective communication.
- Collaborate with engineers, product managers, and researchers to deliver top-quality products.
- Stay informed about the latest trends and advancements in AI and computer vision.
- Engage with stakeholders to translate business requirements into technical specifications.
- Promote AI adoption among internal and external audiences through education and advocacy.
Required Qualifications:
- Bachelor’s degree in Statistics, Data Science, Computer Engineering, or a related field; a Master’s degree is preferred.
- Equivalent experience and education that demonstrate the capability to fulfill the role's essential functions may be considered.
- At least 5 years of experience in developing and deploying AI/ML solutions, with expertise in NLP, computer vision, or deep learning.
- Proven experience delivering production-ready AI/ML models, including scalable data pipelines and monitoring systems.
- Experience in developing AI systems for customer-facing products.
- Hands-on experience with MLOps, including model deployment, versioning, and monitoring using tools like Azure ML, SageMaker, MLflow, or Airflow.
- Proficiency in Python and SQL, along with frameworks and libraries such as TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, Pandas, OpenCV, and Docker.
- Strong understanding of statistical modeling and machine learning techniques.
- Experience deploying models on cloud platforms such as Azure, AWS, or GCP.
- Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
- Demonstrated leadership and mentoring abilities, with strong business acumen.
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