Key Responsibilities:
Lead the development and maintenance of AI/ML-enabled applications.
Design and implement machine learning algorithms and statistical models.
Collaborate with software developers, data engineers, and domain experts to integrate intelligent features into business applications.
Conduct data analysis, preprocessing, feature engineering, and model evaluation.
Monitor model performance and implement model retraining pipelines.
Translate business problems into technical solutions using data-driven approaches.
Stay updated with the latest research and advancements in AI, ML, and data science.
Required Qualifications:
Bachelor s or Master s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
3+ years of hands-on experience in AI/ML model development and deployment.
Proficiency in programming languages like Python, R, Java, or Scala.
Experience with frameworks like TensorFlow, PyTorch, Scikit-learn, Keras, or MLlib.
Strong understanding of data structures, algorithms, and software development principles.
Familiarity with cloud platforms (AWS, Azure, GCP) and ML Ops tools is a plus.
Experience working with large datasets, APIs, and real-time data processing.
Desirable Skills:
Knowledge of Natural Language Processing (NLP), Computer Vision (CV), or Deep Learning techniques.
Experience in Big Data technologies such as Hadoop, Spark, Hive, or Kafka.
Strong problem-solving abilities, communication skills, and a collaborative mindset.
Keyskills: Computer vision Data analysis Machine learning SCALA Data structures Data processing Application development Analytics Python
The key to managing complex infrastructure is not necessarily about the technology that powers the environment, but rather about the people, systems, and processes which successfully support it on a daily basis. Consistent execution in the management of an IT infrastructure translates into the confi...