Are you looking for an exciting opportunity to solve exciting business problems in the domain of Network infrastructure? You will be expected to apply your strong curiosity for data and your proven track record of successfully applying rigorous scientific methods with a proficiency in ML Engineering and DevOps capabilities. This is a unique opportunity to apply your interdisciplinary skills and have a direct impact on global business. 

As an Applied AI/ML Lead within our dynamic team, you will spearhead the development and implementation of AI/ML solutions to address intricate business challenges. This role offers an exciting platform to utilize your keen interest in data, your expertise in ML Engineering and DevOps, and your multifaceted skills to make a significant impact on global business. You will work in collaboration with cross-functional teams, design and develop AI/ML models, and oversee their deployment into production, all while handling vast amounts of data.

Job Responsibilities:

- Develop and implement AI/ML models and algorithms to solve business problems.

- Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.

- Design and develop data pipelines to preprocess and transform data for AI/ML models.

- Train and evaluate AI/ML models using large datasets.

- Optimize and fine-tune AI/ML models for performance and accuracy.

- Deploy AI/ML models into production environments.

- Monitor and maintain deployed models, ensuring their performance and reliability.

- Stay up-to-date with the latest advancements in AI/ML technologies and techniques.

- Be responsible for designing graph data models specifically for algorithm optimization.

- Be responsible for designing and adding the data from the physical and logical infrastructure components and their relationships.

- Developing and implementing data ETL pipelines within AWS 

Required qualifications, capabilities, and skills:

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Atleast 5 years of demonstrated experience in applied AI/ML engineering.

- Strong programming skills in Python, with experience in developing and maintaining production-level code.

- Experience with designing and implementing graph databases, such as Amazon Neptune, TigerGraph.

- Proficiency in working with large datasets and data preprocessing.

- Solid understanding of AI/ML algorithms and techniques, including deep learning, reinforcement learning, and natural language processing.

- Familiarity with AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras.

- Experience in creating infrastructure graph data models

- Experience with cloud platforms, such as AWS or Azure, for deploying and scaling AI/ML models.

- Experience with ETL tools such as Airflow, and Jenkins. Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills. Knowledge of infrastructure operations

Preferred Qualifications, capabilities and skills

- Experience with distributed computing frameworks, such as Apache Spark.

- Knowledge of graph-based AI/ML algorithms and techniques.

- Familiarity with DevOps practices for AI/ML model deployment and monitoring.