Develop and optimize machine learning models for classification, regression, clustering, and recommendation systems.
· Implement deep learning architectures using frameworks like TensorFlow, PyTorch, or Keras.
· Preprocess and analyze large datasets to extract meaningful insights.
· Fine-tune models for performance, accuracy, and efficiency.
· Deploy ML models into production environments using cloud platforms (AWS, Azure, GCP) or edge devices.
· Collaborate with data engineers to build robust data pipelines.
· Conduct research on emerging AI/ML technologies and apply them to real-world problems.
· Write clean, maintainable, and well-documented code following best practices.
· Perform model evaluation, A/B testing, and error analysis to improve performance.
· Work with stakeholders to understand business requirements and translate them into AI solutions.
Requirements:
- 2-4 years of experience in AI/ML development.
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, or Keras.
- Strong understanding of Machine Learning algorithms, deep learning architectures, and statistical modeling.
- Experience with data preprocessing, feature engineering, and model optimization.
- Familiarity with big data technologies (Spark, Hadoop) and databases (SQL, NoSQL).
- Understanding of NLP, computer vision, or reinforcement learning is a plus.
- Ability to work both independently and collaboratively in a fast-paced, agile environment.
- You have an eye for detail, esp. around user experience and secure coding practices.
- A strong drive to learn and explore.
The Ideal Candidate:
- Is by nature highly team-oriented and collaborative. Believes the best work can be achieved when a talented group of smart people work effectively together.
- Has proper understanding of semantic markup and knows how to build interactive pieces that comply with web accessibility standards.
- Has personal projects or frontend related code contributions to open-source community and actively publishes on web development related development topics
