Overview
We are seeking a highly skilled and experienced Senior AI/ML Engineer with 3-5 years of hands-on expertise in developing, optimizing, and deploying machine learning models at scale. In this role, you will lead AI-driven initiatives, collaborate with cross-functional teams, and contribute to the research and development of innovative ML solutions. You will be responsible for designing robust architectures, optimizing model performance, and ensuring seamless integration into production environments.
Responsibilities
- Design, develop, and deploy scalable AI/ML models for real-world applications.
- Lead research and implementation of advanced machine learning and deep learning techniques.
- Optimize model performance, inference speed, and accuracy for production environments.
- Develop and maintain end-to-end ML pipelines, including data preprocessing, training, evaluation, and deployment.
- Work with large-scale datasets, ensuring data quality and preprocessing optimization.
- Collaborate with software engineers and DevOps teams to deploy models using MLOps best practices.
- Implement and integrate ML models with cloud platforms (AWS, GCP, or Azure).
- Stay ahead of industry trends, emerging AI technologies, and best practices.
- Mentor and guide junior AI/ML engineers in model development and deployment best practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 3-5 years of hands-on experience in developing and deploying AI/ML models in production environments.
- Strong programming skills in Python with expertise in ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Extensive experience with deep learning architectures, including CNNs, RNNs, Transformers, and GANs.
- Expertise in working with structured and unstructured datasets for AI/ML applications.
- Proficiency in data engineering, feature selection, and model optimization techniques.
- Experience with distributed computing frameworks such as Spark or Dask.
- Strong understanding of cloud-based ML deployment using AWS SageMaker, Google Vertex AI, or Azure ML.
- Proven track record in building and optimizing AI models for scalability, efficiency, and accuracy.
- Ability to translate business problems into AI-driven solutions and drive project success.
- Excellent problem-solving, analytical, and communication skills.
Skills
- Expertise in machine learning, deep learning, and neural network architectures.
- Strong knowledge of supervised, unsupervised, and reinforcement learning techniques.
- Experience with real-time AI model inference and optimization.
- Proficiency in data visualization and analysis using Pandas, NumPy, Matplotlib, and Seaborn.
- Strong background in natural language processing (NLP) and computer vision (CV).
- Hands-on experience in deploying AI models using Kubernetes, Docker, and CI/CD pipelines.
- Proficiency in SQL and NoSQL databases for AI/ML model data management.
- Knowledge of edge AI and federated learning is a plus.
- Familiarity with Explainable AI (XAI) and ethical AI considerations.
- Ability to mentor and lead AI teams in developing scalable and efficient solutions.
