Key Responsibilities:
- Lead the design, development, and deployment of machine learning models and solutions.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Oversee the end-to-end machine learning lifecycle, including data collection, preprocessing, model training, evaluation, and deployment.
- Ensure the scalability, performance, and reliability of machine learning systems.
- Mentor and guide junior data scientists and machine learning engineers.
- Stay updated with the latest advancements in machine learning and AI technologies and integrate them into projects.
- Communicate complex technical concepts to non-technical stakeholders effectively.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Proven experience in leading machine learning projects and teams.
- Strong programming skills in languages such as Python, R, or Java.
- Proficiency with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and deploying machine learning models in production.
- Excellent problem-solving skills and the ability to work in a fast-paced environment.
- Strong communication and leadership skills.
- Good understanding of MLOps and big data management methodologies.
- Experience in computer vision, neural networks, and reinforcement learning.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 8 to 10 years of hands-on experience in machine learning, deep learning, and computer vision.
Preferred Qualifications:
- Experience with cloud platforms such as AWS, Google Cloud, or Azure.
- Knowledge of big data technologies like Hadoop, Spark, or Kafka.
- Familiarity with DevOps practices and tools.